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

Strategy #10: Use constraints that minimize work and maximize results

Every retailer has limitations to what they can or want do in the process of allocating. Generally we refer to these limitations as constraints. For purposes of our allocation discussion we’ll discuss constraints in two categories:

Physical constraints

These are things that exist as physical limitations which may need to be considered in the process of allocating. Examples include capacity constraints such as shelf or rack capacity, eligibility (whether or not a store is eligible to receive an item at all) and packs and pre-packs. Physical constraints are facts that must be understood and considered to make the best choices in any allocation situation.

Operational constraints

These are things that we as allocators impose to ensure that the volatile nature of allocated merchandise does not cause our system’s recommendations to go too far in a given direction. Examples include mins, maxes, caps and target time supplies. Operational constraints are generally required to compensate for areas that allocation systems are unable to consider or understand otherwise.

Generally all constraints can be thought of as challenges which make the allocation process more complex. They are typically cumbersome to manage and often get in the way of allowing your system to make optimal decisions. So how can we best use constraints to minimize work and maximize results?

What you can do now

Ease up on the constraints. If you’re using better criteria, thus enabling your system to drive results more representative of what your stores need, the requirement for constraints is reduced. Here are some examples:

Physical constraints

Eligibility – tends to be binary (on or off) so there is typically not a lot of opportunity here. If, however, you are using eligibility to reduce stores in an allocation due to limited supply of stock, consider not doing that and rather letting demand determine who should be included.

Capacity – is often used as a max constraint. While this makes sense logically, be sure you’re considering the selling of inventory between the time you’re allocating and the time the new stock will hit stores. Your current inventory will be reduced during this time opening more capacity by the time the allocated inventory arrives. You should also monitor how often capacity is imposed. If it’s frequent, it may be time to consider giving the product more space.

Packs – are typically handled with rounding rules. If you have the option, consider using different rounding rules for different types of product. High ticket items and large or space consuming items are good candidates to round down more aggressively (reduce potential markdown or carrying costs) while high volume and inexpensive items are good candidates for rounding up more aggressively (less financial exposure)

Pre-packs – also generally rounded. If you have the option to configure your system to consider each item individually then do rounding based on total over or under, that is more effective than executing at the aggregate of everything in the pack. See also the note on size at the bottom of this post.

Pack Optimization – You may also have, or be considering, pack optimization options. Ideally this process should be evaluating the financial impact of pack decisions. In the case of pre-pack optimization it’s important that size profiles always be fresh. The assumption that size activity does not change within a season is false and should be challenged aggressively. Update profiles as often as time permits.

Operational Constraints

Mins & Maxes – Widen these wherever feasible. Lower mins avoid overstocking the lower performing stores. If you’re setting mins to ensure presentation, make sure you’re considering presentation for the lowest volume / space combination for the level being set (i.e. cluster). Similarly, max’s should be capping only the most extreme cases at the top of the volume for the level (i.e. cluster) that they’re set for.  Some systems can actually take chain level min/max’s and automatically modify them across volumes enabling you to set them at an average while the system grades them across individual volumes. This can achieve the same result with less effort and more intuitive parameter setting.

Caps – If you’re using a calculated trend that must be capped, these caps should be set for groups of stores (i.e. volume clusters). They should be set letting lower volume stores chase trends more aggressively since the impact is likely to be as little as one case. Higher volume groups should constrain the trend more aggressively to ensure they don’t overreact to a trend that may result in damaging overstocks. If you must set caps at chain, err on the side of caution by setting them as you would for high volume stores. There’s too much volatility, therefore exposure across your store base.

Time Supplies – If you must allocate to a time supply of inventory, do the pre-analysis to determine what an effective target is. If you have the inventory to achieve six weeks of supply (WOS) but tell the system to allocate twelve WOS, you’re forcing it to make unnecessary balancing decisions that negatively impact the result. Determine what WOS can result with the existing and available inventories first, then set the target.

What you should consider when looking for new capabilities

Today’s technology has evolved to the point that many of these constraints can be reduced or eliminated. In some cases that’s due to considering and automatically optimizing them as components of the allocation. Awareness of physical constraints are a fact that can often be interfaced in to allocation from other sources (Warehouse, Order, Assortment or Space systems etc.). Operational constraints are often reduced to just those requiring intuitive input. Presentation requirement defined as a min being a primary example. Once that minimum quantity floor is established, executing to a targeted objective such as achieving profit, revenue or service goals accommodates many if not all other constraints in the process.

Note: Size is sometimes considered in a category similar to constraints. It is a subject that deserves to be covered in and of it self. We have posted some thoughts on the topic HERE.

<< Previous post in series | Next post in series >>

Learn more

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.

Subscribe to receive weekly updates of this series HERE»

Download this blog as a PDF»

For resources on allocation, visit: http://quantumretail.com/solutions/allocation-replenishment/resources

1 person likes this post.

Unlike