MYTH #3: Business Intelligence (BI) solutions are an effective tool to help execute on real-time demand
TRUTH: In reality, BI solutions alone can help you glean answers from real-time data, but they do not inherently have the ability to execute on those questions, and have a difficult time integrating with your existing systems.
Business Intelligence can be described as the process of enhancing data into information and then into knowledge, from that point, the execution occurs based on what you do with that knowledge. Because of the lack of execution from BI, solutions often fall flat. In fact, “more than half of all BI projects are either never completed or fail to deliver features and benefits that are optimistically agreed on at their outset,” said a spokesman from Atre Group. “There are many reasons for this failure rate: high cost of ownership, lack of ease of use, organizational issues, lack of measurable benefits, benefits restricted to few users, a lack of scalability and so on.” However, there are benefits that can come out of BI, but it must be strategically integrated with retail processes that are driven by merchandising objectives, comprehensively deployed and adopted, and managed in ways that produce meaningful, measurable and credible results.
Too much data
Most retailers have vast amounts of data coming from too many sources. “The theory is that the more you know about your customers and the business problem you’re trying to solve, the better you’re able to solve it,” said Karen Parrish, VP, worldwide sales, BI solutions at IBM. “But by trying to access data from too many sources — data that resides in their own organization, data that resides externally, data that they purchase and bring into the organization, data from the Web and data that sits in e-mail — companies may be shooting themselves in the foot.”
Today one of the biggest challenges retailers face is managing the sheer wealth of data available and selecting what is relevant. “Retailers have always gathered an enormous amount of data, but they don’t always use it very well,” says Jan De Joung, Microsoft’s worldwide retail industry solutions manager. The user must make certain that they are asking the right questions of the data. Instead of looking at how much of a product sold at this time last year, it is more important to look at how much of that product is selling now. When you look at those sales, it is also important to look at not only the maximum sales, but also where you had out of stocks, to understand how much of that product you could have sold. With all of the data available to you, you need to know what information you need to make the best decision, typically this is based on the product’s strategy.
“In the past, BI solutions would tell a retailer some of the facts, such as, ‘you have sold this number of this stock and you made this margin’, but didn’t tell them where they lost margin, in the sense that they didn’t have the right product with the right availability,” says Paul Makin, sales director at K3. “The sophistication of today’s solutions allows people to do far more of that investigation work.”
Real time intelligence
Decisions about short life inventory investment often need to be made months in advance, something that can only be done with access to accurate up-to-the-minute data. “It’s near impossible for any person to get their head around how a decision they’re about to make will effect the entire business,” says Roy Lee of Cognos. “Technology provides an environment where all of the criteria can be entered, the business rules and the business assumptions can be modeled, and those ‘what if’ scenarios can be effectively managed and worked through.” This type of business intelligence, when utilized at the lowest level possible (SKU/store) can immensely increase execution success.
Especially for the fashion sector, accurate and up to date information must be immediately accessible. “The fashion sector is characterised by the frenetic way it has to manage its own business,” says software developer Cesare Dania. “At every trade season, everything starts again and the times are cut drastically. As a consequence, to get information in real time becomes vital.”
Turning intelligence into action
But even with this real time data, if a retailer does not have a strategic and efficient way to act on the data, it’s impact is diminished. However, there are sophisticated new systems that give the user the ability to set up minimum constraints for their product performance that will create alerts when performance falls below those constraints, meaning that they can simplify their time by focusing on the areas of their merchandising process that need attention. The most sophisticated systems available can even use the BI it takes in from SKU/store data, and automatically review the data it needs in order to make decisions and recommendations about what to send, how much to send and where to send it. This is the most advanced way of integrating BI with inventory execution.
Integrating BI into an end to end merchandising solution: Quantum’s approach
BI mixed with strategic merchandising and automation
With Quantum Retail’s system, Q, we combine the business intelligence from product data with automated merchandising processes through a shared pool of knowledge that we call Qi. We follow a strategic approach to merchandising, requiring users to to assign roles and goals to each of their products that will be used to create minimum constraints for every product at every store. Then Qi engine continuously monitors and learns from customer behavior over time, automatically reacting and executing on product objectives to ensure that availability is maintained according to the guidelines set for each product.
Users are not asked to choose the correct data 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.
Constant learning
Unlike other solutions, the value and intelligence of Q constantly improves as the Qi engine learns from product behaviors. This means that the value of Q will only increase with time. Item profiles in the Qi engine are constantly updated by the system whenever new data is available, allowing it to accurately predict how that product will act with the intelligence of how it has acted before, while taking into consideration how it is acting now.
Real demand visibility
Q gives you visibility of the real demand in your stores now. With the understanding of lost sales, Q prevents you from missing opportunities so you can capitalize on every potential sale. The Qi engine learns from how your product is moving right now, so you do not need a year’s worth of data to predict how a product will perform. By continuously tracking 35 performance metrics, such as: average demand, average sales, seasonal affects to product life-cycle patterns, shelf life, maximum sales per day, average inventory by date, in stock and in transit, this lets retailers calculate potential consumer activity and demand every day.
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To learn more about Q and it’s constantly learning Qi engine, visit: http://quantumretail.com/q-platform/qi-engine
For more information about BI, check out these On Windows articles:
“6 Tips for Getting the Best out of BI”
“BI Strategy in Retail”
