The Profit Lab: Allocation Metrics that Matter

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

Strategy #9: Go beyond sales and inventory units to factor profitability and other metrics into your allocations

When allocating in retail we’re ideally executing to a specific objective as described in our last post. That objective can be a variety of things including maximizing sales, maximizing service, maximizing profit or something similar. In reality all of the various possible objectives are all intertwined.

Focusing on just one metric may allow you to maximize it, but without visibility to and consideration of the others it is likely that you will sacrifice something more than would be ideal.

Conventional allocation solutions are generally unit based. As such they are able to attempt inventory or sales focused objectives but they have little or no visibility to financial metrics of sales, inventory and especially profit. This imposes a severe impediment to achieving the most basic of objectives in retail. Maximizing profit.

In addition to this, conventional allocation calculation capabilities tend to focus on one unit based objective at best. The most common is to level the time supply (i.e. weeks of supply) of inventory across all stores based on historical selling. The problem here is that say, six weeks of supply in one store may be profitable, the same in another store may not. This is especially true when scarcity and abundance of inventory or packs are a part of the allocation equation. So how can we get to more business oriented goals of getting the most profit or revenue from our allocations?

What you can do now

Assuming you’ve selected a quality base of data using methods discussed in prior topics posted to this series, the next goal is to get as much visibility to the competing metrics as possible. If you are able to define metrics such as dollar volumes or ideally some measure of profit or even simple margin – get them into your view. Even if they aren’t a part of the initial recommendations, they can be used as checks and balances to the result you do get. If possible, utilizing a calculation that impacts profit for overstocking beyond your target can make this even more useful.

Depending on the flexibility of your system you may also be able to consider these metrics in your recommendation calculations. While it may be too complex to create sophisticated logic around the financial results themselves, you may be able to set caps and / or alerts for situations that would create negative financial results. An example may be to cap a shipment where sending another pack would go over target WOS enough to have a negative impact to margin of more than “X%”.

If you don’t have this capability you may be looking at a situation that warrants some external analysis. Screen grabs and spreadsheets may seem remedial, but the time invested can often pay significant dividends for a well thought out process.

What you should consider when looking for new capabilities

The capabilities of technology and mathematical sciences continue to expand. Innovative systems are able to measure both historical and future impacts to financial metrics such as revenue and profitability. When applied correctly they can measure impact across a variety of competing objectives and find the right point to maximize the primary objective (say profit) without sacrificing the others (revenue, service level, availability, presentation etc.). In doing so the answer for two locations which might look exactly the same in historical sales units often result in very different answers that return better results.

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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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