Posts Tagged ‘forecasting’

2012 Retail Outlook-Part 3: Technology is the Force of the Future

Retail Tech Trends

Retail chains are growing. Hundreds of stores, thousands of products, millions of customers, multiple channels with global locations. Retailers cannot remain tethered to past technologies and tendencies anymore. Companies need to innovate and invest in improvements and advancements to stay ahead of the competition. For starters, here’s a look at the top technology predictions for retail in 2012:

Reach for the clouds. Making data available and comprehensive to the consumer is key. Retailers will look to the cloud to get the right data in the right hands.

Technology optimization. While most trends tend to come and go, technology trends continue to evolve and build upon existing technologies. Optimizing inventory deployment for retailers will not only improve margins, but also will maximize markdowns and capture demand, missed opportunities and lost sales.

Embracing the omnichannel supply chain.  As one of the most sought after tech trends of 2012, retailers need to implement a solution that optimizes all channels within a supply chain creating seamless inventory movement.

Two worlds collide. Marketing and technology will converge as retailers begin to understand the value of content and commerce working together.

Ease the payment. Near field communication (NFC) and mobile devices shine in 2012 giving shoppers more, easier payment options.

The voice. As consumers literally talk to their technology devices these days, it’s just a matter of time before 2012 sees retailers using voice control and voice recognition technology to enhance customer experiences.

Technology migrates. Consumers will continue to migrate over to mobile, tablet, smart TVs and game console platforms to make purchase decisions.

These are just a few of the tech trends top of mind for retailers in 2012, some more important than others depending on a retailer’s business strategies. However, below we highlight the biggest, most beneficial technology topics that most—if not all—retailers should embrace in 2012 to get ahead of the competition and to stay ahead of the curve.

The Omnichannel Experience

“Seamlessly integrating the customer experience across all channels of interaction—including stores, websites, direct mail and catalogs, mobile platforms, social networks, home shopping and gaming.”

-Bain & Company

It began with a store. It evolved into a catalog. Then came this thing called the Internet that let brands and companies create websites to showcase products and services. Shortly thereafter, mobile phones became Internet enabled driving the e-commerce boom even further. Now, consumers can shop on any device from TV’s to gaming consoles at any given time. This is the evolution of omnichannel retailing.

Omnichannel isn’t just a buzzword of 2012 nor is it a passing trend. Omnichannel retailing and innovation are here to stay. It’s essentially the only way a retailer can succeed in today’s retail environment, but only if done correctly. Being a truly omnichannel retailer means that consumers have the ability to choose whatever channel they want to interact with, any device they want to do it with, and still get a very convenient, consistent, high-service shopping experience. It also entails flexibility in which a consumer can start the shopping process in one channel (e.g., browsing through a catalog) and complete the transaction in another channel (e.g., making a purchase on a mobile device or tablet) with ease.

However, in the current retail industry, a simple focus on the integrated business process isn’t enough. In other words, instead of just connecting channels, retailers need to blend channels and leverage all touch points – mobile, kiosk, social, brick-and-mortar, TV – seamlessly. It’s the right product, the right price, the right channel and the right time that will deliver a revolution in customer experiences and expectations that will increase margins, drive profit, and provide high service levels for retailers.

Source: Practical Analytics

How to win in an omnichannel world

Retailers who play follow-the-leader will not win in the new world of omnichannel retailing. With a clear vision, a strategy that attributes all channels and devices, and the right technology, these retailers are sure to rise above the competition. A few steps to navigate an omnichannel world:

Inventory planning is key. Proper inventory planning is crucial for omnichannel success. It’s a mix of knowledge, science and processes that have the greatest impact for retailers. A solution that combines these properties will make faster, smarter purchasing decisions, will optimize sales, will minimize inventory carrying costs and will make inventory movement unified – exactly what retailers need to achieve omnichannel status.

The idea for planning inventory for a multi-channel supply chain is to continuously optimize business performance using a deep understanding of item behavior and merchandise roles and strategies to keep up with the rapidly shifting purchasing patterns and the ways in which consumers choose to shop. A retailer’s product mix, locations, sizes, and online efforts all influence omnichannel models. Find a technology that takes all of these aspects into account.

Find more information on making the right moves with inventory planning here>>

Be the best of both worlds. E-commerce has its advantage: it’s huge and continues to grow and evolve, but brick-and-mortar, with its traditional roots, still has winning effects. Retailers will understand the importance of having an online presence as well as utilizing all the other channels that come with it, using technologies that will deliver the right experience to the right people. For instance, Nordstrom allows you to try on and exchange or return any orders placed through any outlet in its brick-and-mortar stores.

With 70% of retailers lacking multi-channel integration, the odds are in favor of the retailers who dive headfirst into omnichannel retailing. Learn more here>>

Gesture-driven Technology

As interactive as it is entertaining.

Gesture-driven technologies were a hot topic at this year’s BIG Show. They have a wide-range of prospects for the future of retailing with capabilities already for data, videos, images and text to be stored and manipulated on interactive whiteboards, projectors and touchscreens with simple hand gestures.

One such technology, the virtual fitting room or virtual fashion mirror, is making brick-and-mortar retail fun again. Popping up all over, especially in the United Kingdom, virtual fashion mirrors allow customers to select from an “endless aisle” of apparel and try it on without removing a single layer of clothing. Shoppers can quickly coordinate outfits by mixing and matching an array of garments and accessories from retailer’s online and in-store inventories.

Another example of gesture-driven tech includes digital signage, which captures attention like traditional static ads cannot. Multi-touch surfaces in store windows put consumer’s images into the ad making the shopping experience more personal by having consumers interact with the ad. Interactive floor ads similarly let consumers engage with the brand with simple movements. Shoppers can search for particular products, try on clothes, and make purchases with the move of a finger.

User interaction with technology is going above the glass. Explicit tools and direct manipulation are no longer needed to drive a user interface. With the ability of technology to see users’ movements in space, gestures are being added to traditional methods in new layers of interaction. However, retailers need to keep in mind that this new technology requires new thinking about dexterity, ergonomics, and whether someone might feel silly or offended with certain gestures.

Pay it Forward

With new priorities come new technologies. Cue the new POS system or, in other words, the mobile device. Mobile technologies will significantly alter the traditional approach to store operations and are a serious game changer for retail in 2012. According to RIS News’ Ninth Annual Store Systems Study 2012, there are two reasons for this:

  1. Mobile technologies are causing retailers to completely rethink the way in which sales associates interact and engage with customers
  2. Retailers are viewing mobile devices as a replacement for the old-school POS suite

Tablets have the most promising growth probabilities with 77% of the Annual Store Systems Study respondents considering purchasing iPads as their mobile platform. Results also showed Apple as the majority leader in the mobile arena. And as consumers continue to outsmart retailers, taking their smartphone with them everywhere they go, retailers cannot only deliver more product information, but can look into sales history to achieve higher service levels with the adoption of mobile technology. Nevertheless, the top function retailers are planning to add mobile devices for over the next three years is mobile POS.

 

Source: RIS News

Price Optimization

Another hot technology topic of 2012 is price optimization, which shouldn’t come as surprise seeing as the number of multi-channel shoppers out there continues to increase and consumers continue to be price-sensitive. 35% of retailers plan to focus on solidifying price optimization technology, as demand-based pricing by store/store cluster and SKU is needed in omnichannel supply chains. More targeted pricing based on individual or household behavior, lifestyle value, social influence, and more factors need to be addressed due to today’s competitive environment and empowered consumers.

Price optimization services will help retailers maximize profit margins while managing information about price changes due to competitor price changes, cost fluctuations, and aging inventory. Achieving top results from price optimization requires a holistic approach that takes into consideration core business concepts. But just as with other business solutions, price optimization is only one piece of the puzzle. It’s just a component of an entire plan. That isn’t to say it should be ignored, but to reap the biggest rewards from it, retailers need to look heavily into forecasting demand components. With forecasting abilities, pricing systems are able to take factors that are not necessarily related to price such as seasonality, events, cannibalization and halo effects, and accurately project the impact of these changes before they happen.

Check out more on seasonality, trends and merchandise behavior at the store, department and product level here>>

Technology represents an outstanding competitive advantage for those retailers who are open to innovation and willing to take on new perspectives of today’s unpredictable, complex retail industry. As supply chains become even more complex and consumers become more engaged and smarter, stay ahead of pack with next generation technology.

Learn how Quantum Retail Technology can adapt your business strategies to the pace of the new retail market.

Look out for our next post on the new look of social and digital media.

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This Retail Life – Part 2: Insider Stories – Building Confidence for Guitar Center

“The advice I would give to executives who are looking to help their company evolve, and to reach their goals, is to really vet out what partner you want to help you do that, and what types of solutions are really required. And if you can find a solution that is holistic to many of your needs – it really can help the company operate far more efficiently than putting in several different pieces.”

LISTEN TO PART 2:

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Audio Transcript

Thanks to our audience for joining us again this week. I am Dan Brown from Mulberry Marketing, San Francisco, and I am joined with Irene Messier, former SVP of Planning and Allocation at Guitar Center, now Heading up the Product Execution Team at Quantum Retail.

Thanks for having me Dan. I’m glad to be here.

So let’s dive right in to what everyone wants to know. How did Quantum win you over? I understand the words “stroke of genius” mean something you…

Um yes – the phrase has somewhat grown to be very near and dear to my heart. First off – I had known some of the founders of Quantum before they formed Quantum and so when they approached me, I had already started understanding how truly talented some of the individuals were behind the creation of this tool. I was at Guitar Center and I was looking for a very different tool. I have been associated with several different traditional replenishment applications. And what was unique at Guitar Center, was the fact that it was $1,000, and $2,000, guitars, and our vendors were using our forecasts to actually plan their production lines and at Guitar Center, they were certainly significantly the largest player in their industry and the vendors were very reliant on good forecasting. When I got there, there was significantly room for improvement.

So I needed something that would give me “the next good order,” if you will. As most traditional replenishment systems do, they look down at the SKU Loc, they figure out what demand might be, and they look over a certain time horizon and cut it or suggest a purchase order. What I needed in a addition to that, was a vehicle that had some real strength behind order forecasting and demand forecasting across long time horizons. And that was one of the things that was very special about Quantum. I couldn’t find it anywhere I looked. So that was probably the biggest reason I engaged in conversations with Quantum early on.

Actually, one of the partners, Mike Hrabe, bought a guitar from Guitar Center, and once I became aware of the fact that, A. He was trying to speak with me, and B. He had purchased a guitar from Guitar Center, now I was dealing with a customer relation issue! It’s a funny story, it’s a joke between us. But yes, he did bribe me, in some respects, to speak with him, and I shouldn’t say that – he purchased a wonderful guitar, and I think his son loved it.

So they actually found me and when I was speaking with them, and the more conversations we had, what was really truly the stroke of genius, was that, I had, as we peeled the onion back, what I was really beginning to understand was that I didn’t have to go buy a replenishment system and a assortment planning system and a long-range forecasting system – what Quantum was able to offer and what Quantum was able to deliver was going to take probably at least two if not three capital requests and roll it all into one. So that’s where the term “stroke of genius” came from. And actually, the correct acronym is F.S.G, meaning “fantastic stroke of genius.”

The F stood for “fantastic,” ha!

(Laughs) Um, the F was really used for something else, but if anyone asks it’s “fantastic stroke of genius.” Which was really, very, very, special, and it was one of the main reasons and selling points back at G.C. to management, to say, hey we’ve got a chance to knock it out of the park. And it was a staged approach – that’s how we implemented it – but it was always with the forethought of having a very comprehensive solution.

You touched on this briefly – but what were they using before? Do you have any retail horror stories prior to using Q?

Um, I can say this because I was responsible for the team, but, we had a few hiccups there. Before I joined Guitar Center, they went from all the vendors sending product direct to stores, to putting in a distribution center, and when they did that they put in an allocation system which was very good. And they had already arranged their merchandising team with the roles of a planner and a forecaster to complement the buying staff – so a lot of the change, if you will, had already started. Going from a singular buyer doing it all, to a more holistic merchandising team, with skillsets that balance each other out, but what was evident when I got there, is that when we were looking at procuring product, and it was in a monthly cycle, so the vendors got a bunch of orders once a month, well what was driving that, and the methodology behind that was based in Excel and Access, and I was, you know, wow I wasn’t in Kansas anymore that’s for sure.

You know, you’ve got a multi-billion dollar company there, someone pulling things out of Access and working it in Excel, you know there were times when instead of cutting and pasting the receipt quantity that we wanted the vendor to ship, we’d paste our beginning of period inventories! Luckily – the vendors would call and say, “Are you sure you want this much?” Which of course, we didn’t, and they knew it. And that was one of the opportunities that was very visible when I got to Guitar Center.

There were many, many, vendors that were very, very, unsatisfied with the quality of the forecasting of the products demand. And back then – it required a lot of hand-holding and the buyer got involved and the vendors were involved, in fact, the first week I was there, one of our major vendors, actually our largest vendor at the time, spent a week in our executive board room going over SKU by SKU, each SKU’s forecast for the fourth quarter, and that isn’t what the buying team should be doing and it certainly isn’t what the vendor should be doing either. So there was definitely an opportunity to help the existing staff and the developing staff to provide a better tool that gave them a far better answer, a more sustainable answer, an answer that everyone could have a higher degree of confidence in.

So were you already looking for a new school solution? Or did you feel like you became a “change leader” for the company?

Um, yes they had been looking for a solution like Q, in fact there was some money saved aside in their budget to address that. The expectation was – you know, let’s go out and get the basic type of replenishment system, and I was able to communicate – that if all we sold was sticks and strings, that had a very high rate of sale, a very stable demand, and the vendor had a really strong supply chain – that those systems would be outstanding and our search would be over very quickly. But that was not the bulk of our revenue, and it would not address the instability in the long range forecasting because those systems today wouldn’t be able to provide that.

So there was a change agent needed in that respect, that while the teams were somewhat organized we needed to provide a tool, and to create a process such that the output was one that again, people were confident in, and then people could go back and people could do the jobs that they were really employed to do.

A buyer could go out and negotiate with the vendor great costs, a financial planner could do the open to buy and manage the quote un quote checkbook, if you will. And the forecaster really could focus in on doing the forecasting and ordering of the product.

And once we were able to deliver that and people understood, Oh, not everyone has to look at this? We actually got a good team and the team has individual roles and when there was confidence that we could all do our individual role very well, there was a lot of change that came out of that. There was a lot of ability to really leverage the existing staff in ways that we didn’t before, because everybody was so focused on – do we have the right forecasts out there so the vendor can go build the product?

Once you chose Quantum – being their first customer – you must have built a strong relationship from the start – could you talk a little bit about that?

Certainly. Again, I’d known some of the principles before they started up Quantum and I knew how talented they were and still obviously are. What is incredibly unique about Quantum is that everybody just kind of roles up their sleeves a pitches in, and even today, you can have an idea or want to bounce something out and have a shower thought, if you will, and you can approach Mike Hrabe or Vicki or Linda or Chris or Morgan and say – hey I was thinking about this – what do you think? And they really do want to hear and be engaged in how we’re maintaining, supporting, and developing their “baby” and it is very, very, refreshing in today’s environment to work with a company that you can feel that vibe, it’s being a part of something really special and dynamic.

And from way back on when we were the first customer, they were obviously fully engaged with doing things right down to asking us – hey, what’s the process flow going to be? You know – we’ll provide this tool – we’ll have alerts and work flows etc., but how are we really going to use it? Really challenging Guitar Center to think things all the way through – and re-question themselves, and go the extra mile to make sure that when we put pieces in – they were fully vetted, not only from Quantum – but from Guitar Center – and they really work – I think that is one of the key differences with Quantum as a solution provider.

When you provide a solution, if it’s not easily integrated and accepted into either the existing process or the processes as they evolve, then your solution is not optimized. And being one of the first customers of Quantum, I was able to witness first hand the principles themselves – living that attitude – that we are definitely in it together – we are here to provide a solution with you and for you – and we are both going to figure it out as we go. And I can honestly say that approach and that feeling is still evident at Quantum today – which is neat.

When you sat down with Quantum early on – how did you decide on the strategies that you would be using?

You know it’s funny, at a former retailer, I won’t use any names, one of the approaches that they took was to do portfolio management during their business planning cycle. And not every category was a stake in the ground, and not every category was a loss leader, or a traffic builder, so I was very much already accustomed to the approach that when you are planning or doing something in business that you don’t treat everything you are affecting the same way.

So for instance at this past retailer if you were a stake in the ground, you probably got more advertising, you were probably not challenged as much to increase your gross margin return on investment (GMROI), because you were a stake in the ground relative to that company, to that product offering the company had in the industry.

So dial ahead – many, many, years later, I’m working with Quantum Retailer, and one of the very unique aspects of Quantum Retail is that they don’t try and have you treat every item the same way, but you don’t have to turn a thousand dials and dial in everything in uniquely for that SKU. Whether you have 10,000 SKUs or 80,000 SKUs you can’t do it that way, or at least it’s not very effective that way.

So what the strategies allow people to do is to say, okay – I don’t bring items in to my assortment for the same reason, every item has its own reason for being part of the assortment. So because I was accustomed to that thought process already, it was a very natural and easy step to take it down to the item level. With Q, we would assign a strategy to an item, and the system would take that strategy and affect the order processing and the management of the inventory level accordingly. So I didn’t have to tweak a thousand dials to get it right. There were items that we wanted to maximize profit, there were items where we wanted to be more aggressive with sales, there were items that just rounded out the assortment that would maybe not be in every door, so I was more than happy with a little bit of a lower service level to achieve other objectives.

So in trying to get Guitar Center to understand the strategy approach we, at Guitar Center, got the merchandising management team together and we spoke. I said, well why do we bring different items in? And it seems like a silly question to be asking, but it was actually a very, very, good conversation. And the head merchandising, and the vice presidents of each of their areas felt very engaged, and felt as though they were defining how we were going to be managing the inventory flow and managing our business going forward.

So it allowed us to A. Be very surgical at a very high level, at an item level, and B. Allowed an opportunity for the merchandising teams’ executive team to be fully engaged, which was really very powerful.

So the strategies that you chose for each product are automatically kept up by the system – did the automation factor make you nervous, or what is it about that word that scares some retailers?

Well you know, there can be an expression – everybody has a little black box – all these software companies have a little black box. And you put information in, you don’t understand what happens, and then it outputs something and you’re supposed to execute your business on the output. And so for automation, particularly, in the role that I had, SVP of Planning, there and in another company, you’re looked at and you’re responsible for providing solutions that are obviously credible. It seems like a stupid thing to say, but the fear is, well if I can’t explain every single thing the system does and the automation just happens, how am I going to be sure it’s going to do everything I want in every single situation.

And you know what – there isn’t a solution that does everything absolutely perfect in every situation because for example – you could have an item that sells once every 26 weeks and all of a sudden in a month it sells two. And go figure. No system is ever going to forecast that, because it’s an aberration, if you will.

So one of the things that you need to get comfortable with – is you have to make sure that you are putting enough due diligence in, to test enough scenarios and conditions that your people operate under – scarcity of product, abundance of product, variability of forecasting, stores going into remodels, and you know, just everything that you could imagine that might impact the stores ability to sell product or the natural demand of the product. If you’ve done that and you’ve fully vetted that out, then you can say, ok you know what, the, well it isn’t a black box, but you can say that if you have 10,000 SKUs across 200 stores, no human being can do that calculation every single day when they’re doing allocation. Or you know, twice a month, when they’re re-looking at the ordering processes.

You need to have a system that can understand and do the math and the automation at the SKU Loc level, because that’s where it’s really happening. And you need to have faith that the system that’s doing that gives you the ability to – at a higher level – to go in and understand what’s truly driving the applications that are truly running your businesses.

And Quantum allows you to do that. They give you alerts, they give you work flows – you can go in at an item level and understand what’s going on. You know one of the things with Guitar Center very early on – if we were at an X number of weeks worth of supply and it looked like we had enough product out there – we could have been understocked in half our stores and overstocked in the other half of our stores. Well no human being is going to go through or could they, with hundreds and hundreds of SKUs, go through and say ok I’m going to order this product – well let me go through, by store, and see what they need and aggregate that up. It would have taken way too long.

So that automation of understanding what’s going on at a very low level and raising it up and providing someone with what is going on in a digestible format in a format that gives them alerts and work flows to understand so they don’t have to look at every single product. Because the product is operating dead on to the forecast, and the service levels are more than acceptable, there’s no reason to go in and spend a half an hour looking at that SKU. You might have to spend half an hour looking at another SKU where there could have been cannibalization or where there could have been a product entering the end of its life cycle, etc.

So that’s what the automation piece does. People at times want to be able to say that they know every single algorithm driving everything, and you’ll get bogged down in doing that. And once you have the comfort level that the application is going to execute its math, if you will, in a way in which you would expect it to, in a way in which you affirm, and then just take it from there, and then you free up your team to really start doing analysis – you’ve got forecasters going back to buyers saying, hey you know what – this SKU looks like it might be entering its end of lifecycle. Or you know what, this SKU is really taking off – and this is what I’m seeing, it’s tripped an alert three weeks running, lets go in and see what’s happening. And the buying team really starts getting very engaged because they have a growing comfort level in that, wow, I have somebody and some thing and some process that’s empowering me – and I do not need to not invest thousands of man hours doing it – but I have a vehicle and a process and a team that’s going to be able to give me this critical information and they go back and work with the vendors and its just a great cycle that you get into.

And you have a story about a big alert you received, right before the recession, don’t you? Can we hear that story?

It was the “Mother of Alerts,” what happened was – it was August and at Guitar Center in August, every SKU’s fourth quarter analysis is executed and because by that time you need to make sure that everything’s I’s are dotted and T’s are crossed. Well what happened was, from the beginning of August to the end of August, we could see the demand softening across the majority of our SKUs. We were beginning to get alerts across the board that said, downtrending, downtrending, downtrending… And what happened was the forecasted orders, and those orders result from a combination of what the current demand looks like, what your existing inventory already is, plus your future orders that you already have coming in.

And within a very short period of time, Q was saying hey – you need to cut back your orders – and it wasn’t a small amount it was a very large amount. And each week we could go in and we could see it happening and – when I answered one of the first questions – about being a change agent, you try and put a process in place and develop skillsets and put a tool in place that allows people to do their job, right? Well – what Q was witnessing and attesting to and serving up to us was so significant that at certain points in time, when you’re in a company such as Guitar Center you need to say, ok – stop, I brought the the head of merchandising in, the executive vice president of merchandising in, the vice president of merchandising in, and I said guys, look at this – this is substantially different than the forecast we gave the vendors a month ago. And you guys own the vendor relationship, I need you to understand this, and I need you to be a partner in this.

I walked into the CFO’s and the President’s offices and said guys, I believe this is rock solid. I can show you this, vet it, forwards, backwards, sideways, every which way you look at it, it is telling us to take this much inventory out and we had already started seeing softening comps, certainly nothing like what was going to happen in the next couple months, but we were seeing it starting to happen. So we sat down with the executives and the merchant community, with the President and CFO, and we all held hands and said, we think this is right. And it was a significant impact.

The buyers grew to understand and have confidence in those forecasts and went and had some tough conversations with the vendors, but I can tell you this – they were some tough conversations, but they were 1000% better than it would have been, had we not have been so proactive about it. One of the things I said to the CFO who was, as he should be during the whole acceptance process and the selling of Quantum at GC, he was very, very, challenging.

And after we put it in, the first engagement, if you will, we happened to deliver everything that was promised, in fact, the inventory reduction that we said would take two years, it happened it in a year, and he called me a sandbagger! But I went in and I said, you know, I want you to understand, if Q wasn’t in place, and I had a staff of people doing this manually, there is no way I would have suggested the amount of reductions that Q suggested, there is just no way I would have had enough confidence in what people were able to do manually, not going down to the SKU Loc level, looking at it at an item level, nor would the buyers have accepted that. Because, if we were wrong, we were leaving some serious sales on the table. And he kind of looked at me and smiled and I smiled back and thanked him for his time and left his office.

But the point was and the point still is, it was never envisioned, when we were trying to sell this solution to senior management, we made claims for service level, for sales, for inventory efficiencies, but we never, ever, even had the inkling to suggest that if a major recession is going to hit, this is going to see it and it’s going to save our skin. Because had we not done that, we would have ordered more than we needed, and we would have had the stores filled to the brim and the vendors would have gotten very very few orders first quarter, and in that vendor community it would have been significant. It would have been extremely hard to have lived through.

So while the buyers went out and had some tough conversations with the vendors, it at least allowed them to be proactive about it, and to have the vendors feel that they were privy to it as well, that they understood and knew what was happening. And I bet the vendors took that information and probably used it in other client sites as well. So I don’t want to call it a happy ending, because no recession has a happy ending, but it was a very gratifying process to actually be able to manage through some very difficult times.

That’s amazing – so after that experience – after you saw that Q really was dead on – did that instill a lot of confidence in the system?

Yes it did. Well that and confidence is, you know what’s the expression, you make money the old fashion way, we earn it every single day. Well, we, Quantum, and it’s application, really had earned the confidence every single day. Even from the pilot. From the initial pilot, within twelve weeks we were up and running and Quantum was affecting forecasts. And within 4-5 weeks – in a test and control environment – we were able to show that the forecasts that Quantum was just spitting out from the beginning, pure vanilla, were 20-25% better than what a human being was producing. And then time went on, and we trained the allocators to use it, and then we trained some of the key members from forecasting to use it, and then guess what? A trained professional with a better tool gets an even better forecast, so then it jumped as high as 29% forecast improvement.

So even from the very beginnings we were able to show very factual improvements, if you will. Another aspect of it – when we launched the Quantum initiative, we formed an executive committee, which had members from the head of the supply chain, the head of stores, so we got the people involved that would be impacted by this solution, and we had steering committee meetings. And every 4-6 weeks you were out there showing them what’s happening, showing them the differences in the processes, showing them the results, and so – you could really see as time progressed, the confidence level building and building and building.

Then once we were able to assess after the implementation of the phase one, which was delivering the order planning, forecasting, and the changes to allocation and replenishment. Basically, we were able to hit all the metrics that were promised in the analysis that was required to approve the project. The president was new at the time and he was in with the CFO as they were grilling me – and he looked over at the CFO and said okay, okay, she’s proved it okay, it works, it’s done it’s job.

(laughs)

So you know, it was icing on the cake. Again it’s hard to be happy about that recession, but it was another way that people at all levels of the company could understand the positive impact that the solution provided the company. And confidence is a great word. It really continued to solidify the confidence.

Awesome. So I understand that you now work with Quantum, can you talk to us about what that’s like?

Sure. You know I mentioned it, I think a little bit earlier. That it is being part of something special. Because it is not just a software application. It is a solution. It is applicable in grocery, it’s applicable in hard lines, it is applicable in soft lines, there is so much power behind what it can do that you really feel good going to work every single day. But really truly, it’s the people. You know, it’s the founders that are still fully engaged, and still very much care about the output. It’s working with a new person coming in and understanding, wow, this really is different, this really does help provide a different way of doing business. It is being a part of that. You know, I feel as though I’ve been part of it from the beginning, but being on this side of it – it’s a lot of fun. I am very grateful. It’s different for me, you know, I was a retailer basically all of my adult life, and so it’s a different set of shoes, but it is lots of fun and I couldn’t think of a company that I would be doing it with other than Quantum.

And we’re running out of time – but lastly, do you have any advice for retailers evaluating new technology like Q?

You know- often times in fact, I was told this – to go out and find the “Best of Breed” – and “Best of Breed” does not necessarily mean that which has been employed over and over and over again. In today’s changing retail environment, it is absolutely critical that when you implement a solution, it should be a holistic approach. There’s definitely some process changes, some system changes, maybe some people re-alignment changes, and you want to choose a solution that is truly going to be part of the solution and is going to be able to work with you as a partner to find the path that is right for that company, at that company’s point in time of its history.

I’ve worked with companies that were at early stages and really wanted to try and grow market share, I’ve worked with companies that were the largest in its industry and were really sure companies and were trying to focus on the bottom line. And at different parts in a companies life cycle they are going to be focusing on different things, you know, driving sales and growing market share – you need great processes and great people and great tools to do that. Optimizing profit and understanding, you’re mature, and you need to be extremely efficient in everything you do – you need some great people and tools and processes to do that too. And Quantum can help you in both scenarios. Which is terrific.The system is very, very, flexible.

I don’t want to sound like I’m trying to sell Quantum here, but the advice I would give to executives who are looking to help their company evolve, and to reach their goals, is to really vet out what partner you want to help you do that, and what types of solutions are really required.

And if you can find a solution that is holistic to many of your needs – it really can help the company operate far more efficiently than putting in several different pieces. If they’re looking to make a lot of changes, that’s probably something you might want to keep in mind.

Wonderful – thanks so much for joining us Irene!

Thanks for having me.

Tune in next week when we will be speaking to Greg Wilson, Director of Field Strategies at Quantum Retail.

Download a PDF of This Retail Life: Changing the Game in Retail»

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Busting the Myths of Retail: #1. Forecasting

This series will cover 5 assumptions that retailers have on the following topics in merchandising: Forecasting, markdown optimization, BI, localization, and time to value. Follow this blog or sign up to receive updates throughout the series.

MYTH #1: If we have a more accurate forecast, we’ll be able to place our inventory better.

TRUTH: In reality, a more accurate forecast alone is only a small part of the puzzle to drive better inventory execution.

The forecast for most product / location combinations for the majority of product is less than 1 unit per week per store. If that value is 0.3 units and a 20% increase in forecast accuracy changes it to 0.36 units how will that change your placement of inventory to support it? In traditional inventory management scenarios it won’t.

Let’s walk through an example: A suburban Walgreens store sells a 3.2 ounce bottle of Degree stick deodorant in Cool Breeze; it has a forecast of .5 units per week. So, the forecast would look like, 1, 0, 1, 0, 1, 0, 1 in the next  7 weeks. While that item may sell hundreds a day across the chain, it sells only every other week at this Walgreens. To execute on this product you either need to guess, or you need to have an objective in place that will help you determine a strategic decision. Ultimately, you need to make a decision whether or not to send a case of Degree Cool Breeze. If they come in packs of 6 and your forecast is .5 units per week, is it profitable to send a whole case? Well, that depends on your strategy.

Creating a product strategy

Product Strategy

Product Role + Objective

Your product strategy is the combination of your product role and objective. The product strategy will drive your inventory decisions and make sense of how you respond to your forecasted sales. When you have a forecast of .6 per week, you are faced with a tough decision, do you send inventory or not? Without a strategy in place for your products, you are just guessing. When you have a strategy for each product, you look at the role of the product, where you are in that product’s life cycle, what the demand forecast is, how much inventory you have in stock and decide if it is necessary to send inventory in order to meet the objective of the product.

Each product within your assortment should have a role:

  • Traffic driver
  • Money maker
  • Image item
  • Core
  • Fringe assortment
  • Loss leader

The role you choose for your products is the basis for your inventory strategy and will be the deciding factor for inventory execution. Every retailer is different, so the roles of your items may not fit these categories perfectly, this is just to give you an idea.

These roles correspond to a specific objective, the purpose of the assigned role:

  • Traffic driver: Maximize sales subject to some acceptable profitability (can be negative profitability in the case of Loss Leaders e.g. milk)
  • Money maker: Maximize profit (High Margin items – Cables at electronics stores – private label basics like tees/tanks at apparel)
  • Image item: Maintain a presentation quantity (specialty appeal: expensive designer dress / 60” leading edge technology flat screen), these items may not create a high amount of profit, but the customer expects to see them when they come into the store
  • Core: Maximize profit subject to maintaining a minimum service objective (everything else – usually a few variations of the objective within this set)
  • Fringe assortment: Capture sales while minimizing markdown exposure (Fringe colors, patterns)
  • Loss leader: A product promoted at a low price to stimulate other more profitable sales

The role of the product will correspond to a specific objective. For example, the objective of core merchandise is to maximize profit by always being in stock, thus you will likely set a minimum service level for this merchandise. If you set 95% as your service level, this merchandise would need to be in stock 95% of the time, even if it would be more profitable to meet a 90% service level, because you have ensured your customers should have 95% availability. If over time it makes more sense to keep up your margin with a 90% service level, you will sacrifice service in this case, but maximize profit.

When you have a forecast of .5 of this item sold per week, and you are running low on stock, you would typically send this item no matter what, if it is essential in your core assortment. Whereas, if you had a role of a fringe item, and you sold .5 of that item per week, you would want to assess where you are in the lifecycle of that product, as fringe colors and patterns may be seasonal. If you are at the beginning of the lifecycle, you might consider sending the product in order to meet the sales through the life of that product. However, if you are in the middle of the lifecycle, it may not be profitable to restock the fringe item because you want to minimize the chance of markdowns.

10 Questions to answer in order to meet your product objectives

  1. What is the role of the product at each store (traffic driver, money maker, image item, core, fringe assortment, etc.)?
  2. What is the goal of the product at each store (maximizing profit, maximizing sales, minimizing markdowns, achieving a minimum presentation quantity, minimum service level, etc.)?
  3. Will your objective change for the product at different stores/clusters?
  4. What is the demand for the product at each store on a daily/weekly basis?
  5. When will each unit sell and in which store?
  6. How will any promotions affect the demand of the product at each store?
  7. Where are you in the life cycle of the product? When will the product be replaced with another line or a newer version?
  8. How much of the product do you have in the DC? How much is on order? How much of the product do you have at each store? How much inventory do you need to put to aside to fulfill the demand for the web channel?
  9. How much of the product do you need to order from suppliers? What is the lead time for the product?
  10. Does the product come in packs? Will you still achieve your objective by ordering an entire pack? Or will you be causing a loss in margin from markdowns?

When you understand what role your products play in your assortment, you will increase the effectiveness of your forecast. Merchandising strategies will assist you from both a financial and a merchandising perspective and ensure that every inventory decision that is made is aligned with achieving your product objectives.

You should continually monitor your products over time to make sure that they are acting like the role you set. Sometimes your traffic drivers become fringe items, money makers may turn into core products. As you’ve seen throughout the recession, the way customers buy products changes over time and you need to react to those changes, ensuring that the roles of your products can meet your objectives.

Take a look at this list of difficult-to-forecast merchandise,

Difficult items to forecast:

  • Big ticket, slow movers
  • Sized merchandise
  • Highly volatile selling items
  • Seasonal product
  • Short life product
  • Perishable product
  • Vendor pack constrained merchandise
  • Heavily promoted items
  • Vendor allocated / scarce merchandise
  • Long lead-time items

These are the items that require the most attention. It will pay off to monitor and manage the strategies you set for them.

New technology for strategic merchandise management

At Quantum Retail, we’ve found that the most successful approach to merchandising is through product strategies. Our system requires you to assign roles and objectives for each of your products. A product is in your assortment for a reason, so we help you determine the most profitable strategies for every product at every store and put them into our platform, Q. Q continuously monitors and learns from customer behavior over time, and automatically reacts and executes to product objectives to ensure that availability is maintained according to the guidelines and constraints set for your objectives.

Users are not asked to choose the correct algorithm or do the math to meet these objectives, the system does that for you – weighing out the proper execution based on the product strategy, forecast and current demand.

Q looks not just at sales, but lost sales as well as other factors like days between sales and when an item sells, does it sell one or more than one and so on. Our forecast has proven to be up to 50% more accurate for our customers than when they used traditional solutions, but when prospective retailers come to us expecting that an accurate forecast will solve all their inventory and stock decisions, we insist they look at product strategies and the importance of accurate allocation and replenishment.

When we say ‘what’s your goal?’ It’s surprising to find that most retailers have no strategy for their merchandise. It’s important to be strategic!

We guarantee that the most accurate and profitable way to place your inventory is not by forecasting alone, but by executing a strategy for each of your products.

Learn more about Quantum’s approach to strategic merchandising: http://quantumretail.com/solutions/q

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Quantum Retail Releases Q v 10.05 to Support Complex Supply Chains, eCommerce, Enhanced Order Planning/Warehouse Replenishment and Forecasting Capabilities

MINNEAPOLIS–(BUSINESS WIRE)–Quantum Retail, provider of the most advanced retail merchandise optimization systems currently available, has released the latest update to its core platform, Q. The update provides advanced execution for complex supply chains, eCommerce, and enhanced order planning/warehouse replenishment and forecasting that allows planners to manage at the day level for short life products and up to 18 months in advance for long life products, with the ability to recalculate distributions based on the most recent localized demand data ensuring extremely accurate allocation and replenishment.

Specific changes in this new version include:

  • Multi supply chain support gives flexibility in order planning/warehouse replenishment and distribution for retailers with complex supply networks and methods, such as Vendor to National Distribution Center (DC), Vendor to Regional DC, National DC to Regional DC, etc. to move stock as quickly and efficiently as possible, reducing the risk of missing a sale due to unplanned circumstances. Q now supports direct to store orders and allows users to view order quantities by location in order to get the right quantity to every local store as soon as it is needed.
  • eCommerce integration enables retailers to easily manage and integrate eCommerce inventory, warehouse or vendor availability and distribution alongside physical store locations. This permits retailers to maintain availability, so that high demand products do not go out of stock either in-store or online.
  • Enhanced order planning/warehouse replenishment and forecasting allow planners to forecast and manage short life products at the day level while users can also change to a week view and manage forecasts and order plans for 18 months out for longer life products. Planners can also test “what-if” scenarios, with the ability to change quantities as late as time of receipt based on the most up to date demand data. This means retailers are able to easily and accurately manage the real-time demand for their inventory all the way down to the local, individual store level with the Q system.

“We took extensive feedback from customers into account when implementing the latest changes to Q,” stated Morgan Day, CTO of Quantum Retail. “This latest release incorporates some important improvements to an already highly robust software offering and we will continue to improve Q to ensure our customers have the benefit of utilizing the most advanced merchandise optimization system available.”

About Quantum Retail Technology, Inc.

Quantum Retail answers the new questions facing retailers with a merchandise optimization suite designed for the increasing pace and complexity of the consumer revolution and today’s competitive landscape. Quantum Retail’s award winning solution, Q, solves the most difficult and costly problems retailers face – quickly and permanently.

The Q solution is the new answer for: Forecasting and Order PlanningReplenishment and AllocationAssortment and Range Planning.

Read more about Quantum Retail»

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The Profit Lab: Using Forecasting within an Assortment Plan

THE PROFIT LAB // 4 Strategies to Optimize Assortment Planning

WEEK 3

I was recently working with a major retailer who expressed that they had so many forecasts available to them that it was hard to know which one to use. There is a forecast for marketing, for the catalog, for the website, one for the replenishment of goods at a low level, one for financial merchandise planning at a high level of merchandise, one for the distribution center, and the list continued. Which one do we use for planning? It was almost enough for them to throw their hands up and just base their plan on last year. I laughed and said that if they did that they would be on par with almost every other retailer out there.

Sadly, my experience has shown that to be true. While forecasting has, to a certain extent permeated the realm of higher level merchandise financial planning it has yet to make a real beachhead in assortment planning. I would argue that there is a lot of opportunity to be gained if the forecast is incorporated into the assortment planning process for determining store assortment breadth, depth, and whether or not items will be carried at all.

Assortment Review

Finding the balance between the benefit of utilizing a forecast in assortment planning or not partly depends on what you are forecasting. When the assortment plan is synonymous with an assortment review process or category review the benefits definitely align with utilizing a forecast. An Assortment review process is most typically used in long life items. Whether they be hardlines merchandise or long life softlines merchandise, such as jeans, the forecast can predict performance of an item with a high degree of accuracy. Traditional forecasting systems require a great deal of history to provide a forecast that has a confidence level that is high enough to be worthwhile to incorporate into the process. Items that have long life, often referred to as replenished items, typically have a confidence level that is high enough. So, the results of a demand forecast, which is a forecast that incorporates lost sales and available inventory, can be utilized by the planner to determine which items should be kept, which items should be deleted, and which items should be added or removed from a specific cluster. Typically this process is completed using only historical performance. However, trends that may not be perceptible when looking at historical performance can be seen in a forecast.

Determining the breadth of the assortment to a specific store, or cluster of stores can also be enhanced by forecasting. By using a forecast to best match a product with clusters that are most likely to sell the item profitably, it is possible to reduce overstocks and prevent markdowns.

Forecasting for fashion

Nobody would tell you that it’s easy to forecast for fashion or any short shelf life product such as cell phones or DVDs. Why is it so difficult to forecast fashion? There are a number of reasons, but the primary issue is short life. Traditional forecasting systems need long periods of historical activity to identify selling trends and begin producing results they have confidence in. Add the complexity of sized merchandise and the data is much too granular to draw SKU / store level conclusions from. Many have come up with complex algorithms, constraints and rules that attempt to address this issue. So retailers have adopted an alternative approach: consolidation. By consolidating the histories of many products that have similarities to the current product, we feel confident that the current product will behave as its predecessors have. For example, when allocating a new product to stores, it’s common to use a base data set of the product’s class, or alternatively, choose a “like item”. This of course is simply a surrogate to address the limitations of forecasting and store replenishment. Since the products don’t live long, we supplement our need for more historical selling time by applying our knowledge of similar products or product groups to give us more data. This allows us to begin seeing selling patterns. We then apply calculations that interpret the relationships in this base of data to derive a calculated recommendation.

These calculations are simpler than forecasting routines, but together with the additional merchandise that makes up the base of data, they are much less volatile and therefore return reasonably stable results. We review this result and change it based on other dimensions of data we analyze, assumptions and intuition. Having said that, there are forecasting systems that have been able to aggregate similarities in products, such as attributes, price points, or fashionability to give a semblance of accuracy to a forecast.

Tracking Life Cycles

Recently, a few companies have had success applying forecasting to fashion allocation. They have done this by combining advancements in technology with innovation in retail science to understand the relationships of behavior across many different products, store types, and levels. Two of these relationships that have shown some promise are lifecycle and strategies. Tracking the lifecycle of an item at a store level to see how that store behaves with a new product that has a short life has shown to be an excellent indicator of future item behavior. A typical product introduction has a curve to it over time that shows how quickly a new product takes off and how long it produces positive results. Mapping that behavior by store to new items gives a solid indication of how a similar new item will perform in the same location.

Product Strategies

With the knowledge of life cycles, product strategies and price points will give the forecast lots of historical data points. Another helpful tactic is to create product strategies. An item’s strategy is defined by how the product is expected to behave or by assessing why the item is in the assortment. Traffic drivers, loss leaders, fringe items and core items are all terms that are typically used to describe an item’s strategies.   The combination of strategies and lifecycles starts to give us a preview of an item’s behavior by store once it is introduced. These can be used to help a planner determine where certain items will perform well in order to determine which clusters are best to receive the item.

Technology to simplify the complexity

With automated inventory management systems, the complex execution can be simplified. Since these systems also understand what you as an allocator are trying to achieve, they can execute to that automatically. Only when they cannot do what you’ve asked of them does the allocator need to intervene. Even then, issues are addressed using business logic rather than trying to manage complicated calculations, statistics or controls.

The same process can be applied to any new item, whether short life or long. By using a culmination of information similar to that product, a new product can be forecasted with enough accuracy that a planner can have a good recommendation as to where that product should be carried. For example, by knowing how fashion-forward an item is, the item’s color, price point, and attributes, such as sleeve length, the forecast can use a consolidation of similar items to forecast how that item will perform in a given store based on that store’s historical performance metrics. If we spend more time finding the data that most closely reflects the trending, lifecycle, seasonality and historical demand of the item we’re allocating, results ultimately improve. Once these metrics are known, a planner can determine if the item will positively impact sales or profit enough to carry it in the store.

Forecasting for localization

The benefits to localization are rarely disputed. All retailers to a matter of degree are attempting to place the optimal assortment in each store based on that store’s propensity to sell. By looking at history alone for a given store the localization process is simply not going to be optimized. In an earlier installment to this topic I wrote about the need for clusters to continually adjust to the behavior of the stores. Stores should not be locked into a particular cluster for an entire season/year but should shift as plans become actuals. Additionally, SKU rationalization or optimization, depending on your definition, needs to be a part of the localization process. As stores behaviors change, items need to be added or removed from the assortment in order to optimize the stores performance.

Forecasting should also be part of the localization process, although not as blatantly as dynamic clustering or SKU Rationalization. Rationalizing of the SKUs should be based, in part, on the forecast of the SKU / store rather than solely based on history. A stores assignment to a cluster should also utilize a forecast to cluster the stores given their expected behavior in the near term. As a caveat, this only works if you are re-clustering the stores on a weekly or monthly basis. Any further out than that and I would not trust the forecast’s accuracy.

Forecasting for depth

The hard part in using forecasting is attempting to determine whether or not to add an item to the assortment and deciding what stores the item will be ranged to. The much easier portion of the assorting process is in determining how many of the items to hold in the store in order to capture expected demand.  A forecast can help determine the depth of the assortment and arguably have a greater impact to the performance of that assortment than helping to determine the breadth. By clustering stores together based on a forecast, the stores that are likely to perform similarly are going to be grouped. Presentation quantity is, of course, a consideration of the depth of the assortment. Typically the planner has the ability to determine how much product goes into the store and does so by the store volume cluster. Using the reliable wedge, the planner will typically put more in the larger volume stores than the smaller ones.  However, if the forecast becomes more reliable, the amount of product that initially goes to the store can be refined to a more granular level so as to avoid over or understocks early in the product’s lifecycle. A good allocation or replenishment should be able to take care of it from there.

In Summary

It’s easy to argue that the forecasts at the SKU/Store level are too inaccurate to be of any use to the assortment planning process, but with some new thinking of how to forecast, significant value can be gained.

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The Profit Lab: Forecasting doesn’t work for fashion, does it?

THE PROFIT LAB // Top 10 Ways to Pull Profit from Allocation

Strategy #5: Overcome limitations to forecasting by using better data

I know many of you believe, like I do, that there should be no reason for separate systems supporting allocation and store replenishment. Philosophically the objectives of these two systems are exactly the same: Get the product you have available to the stores where customers are looking to purchase it when they expect it.

So why do there continue to be two separate solutions for these very similar processes?

Answer:
Forecasting limitations

In over 25 years in retail, with most of my exposure being centered on planning and inventory management processes and systems, I’ve seen numerous philosophies and initiatives come and go. One of the most intriguing has always been attempts to apply the automation existing in many forecasting, replenishment and other supply chain systems to fashion allocation. My memory is littered with examples of attempts and failures in doing this – from both colleagues and personal experience. The few who have claimed success in the past usually measure success as “ability to execute” rather than “ability to achieve better allocation results”.

Why is it so difficult to forecast fashion? There are a number of reasons, but the primary issue is short life. Traditional forecasting systems need long periods of historical activity to identify selling trends and begin producing results they have confidence in. Add to this the complexity of sized merchandise and the data is much too granular to draw SKU / store level conclusions from. Many have come up with complex algorithms, constraints and rules that attempt to address this issue. My experience has been that while these can do a better job than a traditional forecast, that’s really not saying much and the effort isn’t justified by the result.

So, as retailers, we have adopted an alternative approach, allocation. If we look at allocation conceptually it’s mainly a surrogate to address the limitations of forecasting and store replenishment. Since the products don’t live long, we supplement our need for more historical selling time by applying our knowledge of similar products or product groups and use those to give us more data. This allows us to begin seeing selling patterns. We then apply calculations that interpret the relationships in this base of data to derive a calculated recommendation.

These calculations are simpler than forecasting routines, but together with the additional merchandise that makes up the base of data they are much less volatile and therefore return reasonably stable results. We review this result and change it based on other dimensions of data we analyze – and based on assumptions and intuition.

Most retailers have long felt intuitively that we can do better, but how?

What you can do now

Since allocation is generally a mechanism to more simply forecast sales and inventory need, short of implementing a new system we must improve the allocation data and calculations. As discussed in previous posts in this series, spending more time selecting the products we use as the base of data can have profound impact on the quality of allocation results. If we spend more time finding the data that more closely reflects the trending, lifecycle, seasonality and historical demand of the item we’re allocating, results ultimately improve.

Often there is also opportunity to improve our allocation calculations. Many existing solutions have multiple calculation choices, and some even allow us to define new calculations. Most retailers fall into a pattern of using just a small number of these (often just one). This is frequently a symptom of a difficult implementation which resulted in too much change to adopt all at once so the simplest options get used. If you have a system that has been in place for months or even years, you’re past the learning curve of changed process associated with your system. Challenge yourself to understand the objective of each available calculation and experiment with them to see if those you haven’t been using can be made to return better results. Analyze the weaknesses of each and if you have the ability to modify or add to them – try it!

What you should consider when looking for new capabilities

Recently a few companies have had success applying forecasting to fashion allocation. They have done this by combining advancements in technology with innovation in retail science to understand the relationships of behavior across many different product and store types and levels. The resulting understanding of behavior across multiple dimensions is used to derive the likely behavior of the product you need to allocate.

With the best of these systems, even though the underlying logic is much more complex execution has thankfully been simplified. Since these systems also understand what you as an allocator are trying to achieve, they can execute to that automatically. Only when they cannot do what you’ve asked of them does the allocator need to intervene. Even then, issues are addressed using business logic rather than trying to manage complicated calculations, statistics or controls.

Footnote

Replenishment users have long been chasing the elusive “perfect demand forecast”. Interestingly, it turns out that a better forecast is only a small part of getting a better allocation result. In fact taken alone an improved forecast will often have no impact on an allocation result at all. More important than the perfect forecast is how you support it with inventory.

An imperfect forecast can drive a superior result if the decision about how to place inventory in support of that forecast is aware of:

1) The weaknesses that exist in the forecast
2) The objective you are trying to achieve with this product

This will be the subject of an upcoming post to the Profit Lab series on Allocation.

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Follow this series to learn all 10 strategies for improving allocation. We will be deconstructing the allocation process and exploring opportunities to improve within your current allocation processes and technology limitations. We will also review key areas to think about if you are considering investing in improved allocation capabilities.

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5 tips for developing a real-time response plan for customer behavior

By Greg Wilson, Director of Field Strategy, Quantum Retail

1. Set objectives –

Each product should have a role with specific objectives that can be measured and executed to. A product may be in your assortment to drive traffic, to generate profitability, to present an image or to opportunistically acquire impulse sales. Each of these roles come with unique objectives that can result in different inventory requirements.

2. Shift focus –

While forecast accuracy is important, it is not the only way to improve inventory placement. If you are adjusting forecasts to achieve different inventory results, you’re already reacting to this fact. Shift focus to finding the best way to utilize inventory to achieve goals while understanding forecast accuracy and variability are realities.

3. Waste not –

Get a deeper understanding of the impact of waste on your inventory decisions and act on it. Depending on margin, it may be more profitable to accept additional waste on some products, while other products would be better served accepting an occasional lost sale.

4. Get local –

There is no substitute for understanding product behavior at local levels. There are many ways to improve this understanding but consider those which have the most impact including:

Seasonality - If you’re working to static, periodically generated seasonality profiles, you have a great opportunity for improvement.

Time of day – Did you stock out? When? What did that mean in missed opportunities for sales? Can you replenish again today? The more detail you have in answering these questions the more efficient you can make your inventory – especially for short life, short lead time merchandise.

Day of week – Does this location have a weekend traffic boost? Does that product respond to the pattern? Understand these interactions invariably leads to better performance.

Weather impact - Does this product react differently on cold days or wet days? What does that mean to demand? And how should that affect how stores are supplied? If I can ship it tomorrow and I know it’s going to be hot, what’s the right decision? We all know these realities exist, but have you been able to execute to the reality?

5. Revisit and rationalize –

Product behavior constantly changes with the changing consumer. The item that fulfilled it’s role last year or last quarter may not be doing so now. You need to be alerted to situations where this change is happening, and have a mechanism to understand and react to the way that impacts your offerings to customers.

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New Look selects Quantum Retail’s Q to optimize inventory fulfillment on path to growth

Bolt-on solution set to quickly optimize inventory forecasting and replenishment at top fashion retailer

LONDON, UK - Jan, 2008 – Bolt-on solution set to quickly optimize inventory forecasting and replenishment at top fashion retailer. New Look, a leading European apparel retailer known for its fast fashion proposition and leading designer ranges, has selected and implemented Quantum Retail’s inventory optimization solution, Q, to manage the replenishment of its 600 stores.

“As a fast fashion business with our customers at the core of everything we do, we recognized that Quantum Retail’s demand forecast model offered us an opportunity for our customers to further influence our decision-making,” said New Look Director of IT, Adrian Thompson. “It’s innovative science allowed us to continue to support our fast fashion model with speedy and accurate decisions based on our latest sales and stock figures.”

“The compelling business case that supported this investment was based on a number of metrics ranging from stock imbalance, improved service levels and a reduction in markdown,” Thompson added. “Put simply, Quantum Retail is able to more accurately reflect where our customers would like the product and at what level. It effectively bridges the gap between planning and execution.”

Quantum Retail’s Q solution has been implemented alongside the retailer’s existing Oracle retail merchandising system, initially optimizing the replenishment part of the business. Future planned phases include multi channel lifecycle management, initial allocation and reorder planning. vii.

“The successful delivery of this program was based on an exhaustive proof of concept and a speedy implementation,” Thompson said. “The Quantum team integrated seamlessly with my own. Their well thought through designs included system and integration, great business engagement and training at both commercial and functional levels. Quantum is now live with no adverse impact to either IT or the business and is already giving us confidence that the business case will be delivered successfully.”

After an initial monitoring period, service levels showed an increase in availability alongside a reduction in total inventory when compared to a control group. As the rollout of Q continues, it will be rebalancing stock throughout New Look’s 600 UK and international stores, leading to fewer stock outs and improved sales and profit. Through the use of Q’s advanced forecasting and order planning module, New Look will be able to gain greater visibility of long range inventory need and be able to optimally flow inventory to its stores.

“Q uses a proprietary approach that is designed to be the most accurate, responsive and reliable inventory fulfillment tool in the fast-changing world of retail,” said Chris Allan, head of product strategy for Quantum Retail. “At the same time Q has been designed to be a highly practical and useable solution that operates alongside existing systems for simple and quick implementation.”

“Its simple user interface means Q can be used by our allocators, rather than having to rely on experienced forecasters and mathematicians,” Thompson concluded.

About Quantum Retail Technology, Inc.

Quantum Retail answers the new questions facing retailers with a merchandise optimization suite designed for the increasing pace and complexity of the consumer revolution and today’s competitive landscape. Quantum Retail’s solutions solve the most difficult and costly problems retailers face – quickly and permanently. Our Q solution is the answer for: Forecasting and Order Planning – Replenishment and Allocation – Assortment and Range Planning.

About New Look

New Look has 590 stores in the UK and Eire, and 263 stores in France trading under the name Mim. In addition, New Look has 13 branded stores in France and Belgium, and has recently opened franchise stores in Dubai, Kuwait and Saudi Arabia. In the UK New Look has a 4.8% market share, making it among the leading womenswear retailers in the UK (Source – TNS).

New Look also has a growing market share in Mens & Kidswear and is now the number 1 retailer of women’s shoes in the UK by volume, with a market share of 7.3%. (Source – TNS). 25% of British women have bought an item of outerwear from New Look – amounting to over 6 million customers (Source – TNS). New Look’s competitors include H&M, Next, Top Shop and Dorothy Perkins. The average age of shoppers in New Look is 30.

Further information can be found on http://www.newlook.co.uk and Product and Management photos are available upon request.

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Rock Around the Stock: Guitar Center’s forecasts and inventory allocation now make beautiful music together

Taking its cue from the Q system, Guitar Center’s forecasts and inventory allocation now make beautiful music together. Merrill Douglas, Inbound Logistics.

MINNEAPOLIS, MNAugust 2007 – Blues, rock, country, hip-hop, salsa – American tastes in popular music run the gamut. And the sounds that are big in El Paso this year might be totally different from the sounds that are hot in Brooklyn, or Nashville, or Spokane.
So when your business is selling musical equipment, imagine how hard it is to keep each of 200 stores across the country stocked with the mix that’s in tune with the local music scene.

That’s what Guitar Center was wrestling with three years ago. Part of its challenge stemmed from the fact that its stores differ greatly in size, ranging from 5,000-square-foot shops to 30,000-square-foot big box locations.

“Also, the types of customers we deal with vary widely depending on demographic and geographical regions,” says Bret Hayden, director of business process design at Guitar Center, Westlake Village, Calif.

The products that Guitar Center carries – guitars, amplifiers, percussion instruments, keyboards, and professional audio and recording equipment – amount to 7,000 SKUs. To serve customers and keep profits high, the company must understand how each SKU performs in each store. A homegrown forecasting system, developed in Microsoft Excel and Access, wasn’t hitting the right notes.

“The forecasting system operated at the chain level, but we really needed to be looking at inventory at the store level,” Hayden says. “We needed the ability to look at each one of our SKUs, and each one of our stores, and understand how they perform differently from one another.”
In addition to a system that provided insufficient detail, Guitar Center faced another challenge when trying to understand the store/SKU relationship.

The company’s forecasting team used one set of business rules to determine the volume and mix of products to send to its distribution centers, while the allocation team used a different set to create the product mix for stores.

“We would end up with a serious disconnect between what forecasting thought was needed and what allocation thought was needed,” says Steve Johnson, Guitar Center’s director of forecast, allocation and replenishment.

Today, however, Guitar Center integrates forecasting and allocation in a single process, and is much better able to tailor each store’s product mix to local demand. These changes came about through the company’s work with Quantum Retail Technologies.

Guitar Center has served as a beta customer for Quantum, helping the Carlsbad, Calif., software firm develop its inventory optimization solution, Q.  The retailer ran a pilot implementation of Q in late 2005 and early 2006; then entered a detailed design and implementation phase to address its long-range forecasting and product allocation needs.

That version went live in the third quarter of 2006. A third phase of the implementation — adding commodity products such as guitar strings and drumsticks — was due to go live in late June 2007.

Too Much Data

Quantum developed Q to meet the needs of retailers who, over the last few decades, have increasingly moved decision-making responsibilities from store managers to home-office executives. Those executives base many decisions on sales data pulled from the stores. But their enterprise resource planning (ERP) systems can’t analyze such a vast volume of information in great detail, says Mike Hrabe, Quantum’s vice president of sales and marketing. Instead, they aggregate the data and look at average performance for categories of stores and items.

“Through that smoothing, averaging, and aggregating process, retailers have effectively eliminated much of the detail associated with how items behave at the store level,” Hrabe says.

Ignoring the store-by-store detail obscures important information, such as whether a store is stocking the right product quantity, notes Chris Allan, Quantum’s founder and head of product strategy.

“A 98-percent in-stock of a certain product across the chain doesn’t really show a complete picture,” he says. “Some locations may be out of stock for several weeks; others may be overstocked.”

Q uses data from point-of-sale systems, ERP systems, and warehouse management systems to track exactly how much inventory each store has, how fast it’s selling, and how much new stock is flowing through the pipeline. In making forecast and allocation decisions,Q also considers the role each product plays in the company’s merchandising strategy.

A popular product at a marked-down price plays the role of traffic driver, Hrabe explains. The margin is low, but it draws in shoppers who might make other purchases while they’re in the store. Another product, with a higher profit margin, is a money-maker.  Still another serves as an image item, bolstering the store’s prestige by its presence even though few people actually buy it. Think of a giant screen TV in a consumer electronics store, he says.

Products play different roles in different stores. “An image item at the Best Buy in suburban Minneapolis might be a money- maker at the Beverly Hills Best Buy,” Hrabe says.  Demand for products also changes over time. As Q recommends inventory allocations for different stores, it considers the roles the company assigns to different products at those stores; then it tracks the products’ behavior to see how well they play their parts.

More precise information about product demand and performance creates greater efficiency. “Retailers hold too much inventory for fear of losing sales, but over-inventory means lost profits,” Hrabe says.

“Retailers have unbalanced inventory because they use grade group averages and lose much of the detail. They end up with too much inventory at one store, too little at another. Q directly addresses these issues,” he adds.

At Guitar Center, the point-of-sale system feeds data into a JDA Software ERP system, which passes it along to Q. Then, Q’s recommendations and alerts pass back to JDA and to the company’s Arthur Allocation system. “As part of Phase 3, we will integrate Q with our warehouse management system, so we’ll have information regarding shipment delivery times,” Hayden says.

Each time Guitar Center adds a new product to its assortment, the buyer and planner assign it a role and a strategy. “They can also set up other types of parameters,” Hayden explains. “For example, they can plan for a display in the store for that product, or set a ‘max stock’ if the item is big and bulky.”

The company could assign those rules to each product on a store-by-store basis, but executives have decided to move one level higher, dividing stores into several “grades” based on their characteristics. Stores get different grades for different product categories.
“One store could be an ‘A’ store for drums, but a ‘C’ store for guitars,” Hayden says. “We have the ability to manage inventory using those grades.”

Besides helping Guitar Center planners determine what stock to order and how to allocate it to stores, Q monitors product performance in real time and tells planners when product performance doesn’t match the forecast. For example, Q notifies planners if an item is selling better than expected. The planners can then arrange to order larger quantities in the future.

The Missing Piece

Company officials are contemplating a possible fourth phase to the Q implementation, which would focus on assortment planning. “That’s the piece we’re currently missing in our suite of applications,” Hayden says. “We’re able to create strategies for these items, but we don’t have good visibility to how that item fits in the whole assortment.”

Quantum representatives also have been talking to executives in Guitar Center’s Music and Arts Center division, which serves the school band market through more than 90 stores. Since Guitar Center started using Q, service levels and in-stock rates have increased, with a better inventory balance across the chain.

“We don’t have as many over- and under-stocks as we had in the past,” Hayden says. Also, now that it’s monitoring performance at the store and SKU levels, the company can generate more exception reports, and can measure forecast error. Those exception reports are important because they alert planners to problems or anomalies in parts of the operation that weren’t receiving enough attention.

“Q helps maximize users’ time and makes sure they spend their work hours where they can add the most value,” Allan says. And that’s music to Guitar Center’s ears.

About Quantum Retail Technology, Inc.

Quantum Retail answers the new questions facing retailers with a merchandise optimization suite designed for the increasing pace and complexity of the consumer revolution and today’s competitive landscape. Quantum Retail’s solutions solve the most difficult and costly problems retailers face – quickly and permanently. Our Q solution is the answer for: Forecasting and Order Planning – Replenishment and Allocation – Assortment and Range Planning.

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Forecasting For Success

Forecasting is a tricky business, retailers lose money every time a demand forecast is inaccurate. Sophisticated software is necessary to ensure that customer demand and in-stock products are a perfect match.

Dori Saltzman, RIS News – April 2 2007 – Forecasting is a tricky business, retailers lose money every time a demand forecast is inaccurate. Sophisticated software is necessary to ensure that customer demand and in-stock products are a perfect match.

The Guitar Center chose Quantum Retail’s Q forecasting software to help it get a handle on the “fashion-based, choppy demand” of its higher-priced merchandise. Early indications are positive: though Q is currently forecasting only 50 percent of the inventory — representing the vast majority of sales dollars — the forecasts it generates are 20 percent better than before, according to Irene Messier, executive over inventory management.

Prior to implementing Q, the Guitar Center used two separate forecasting systems. One, an automated replenishment system, was used solely on the less expensive, high velocity items — the so-called “sticks and strings.” A manual, excel-based system was used on the more expensive, slow moving items — such as $700 guitars.

The Guitar Center selected Quantum Retail to provide a system to handle both types of inventory. “We were looking for something that gave us better forecast outcome (on the slow moving items) and also hoping to find a solution that could be utilized in updating our auto-replenishment product as well,” says Messier. The Guitar Center upgraded its forecasting methods after identifying a need for greater demand accuracy for the slow-moving items. “One of the factors in a situation where you’re dealing with Excel-based forecasting is that the level of accuracy, due to the amount of information that needs to be processed, isn’t going to be nearly as accurate as using a statistics-based forecasting model,” says John Zavada, executive vice president and CIO.

The $700 guitar is the quintessential high-priced, slow moving product for which accurate forecasts are vital. Guitar Center stores risk unbalanced assortments and lost sales if forecasts are off.

In order to determine that Q could generate accurate forecasts for both the high priced and high velocity items, the Guitar Center ran a six-month pilot before rolling out the system live on the higher priced inventory. The pilot was run on a sub-section of the products. “We observed consistent month after month, better forecasting coming out of the Q application,” says Messier.

About Quantum Retail Technology, Inc.

Quantum Retail answers the new questions facing retailers with a merchandise optimization suite designed for the increasing pace and complexity of the consumer revolution and today’s competitive landscape. Quantum Retail’s solutions solve the most difficult and costly problems retailers face – quickly and permanently. Our Q solution is the answer for: Forecasting and Order Planning – Replenishment and Allocation – Assortment and Range Planning.

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