THE PERFECT FORECAST

The perfect forecast doesn’t exist. However, if you could control the major factors contributing to demand, you could get close to perfection. If pricing is the steering wheel on the car, then smaller factors like suspension, curves in the road, weather, and others can force you off the road. The steering wheel may be as sensitive as a race car going at top speed or have a lot of play as you cruise down a country road, but either way the steering wheel has the biggest influence on where you are going.

If you price to exceed current inventory levels then by definition you are likely to have a very accurate forecast. Unfortunately you will stock out and achieve demand exactly matching inventory constraints. Certainly not the best way to improve forecast accuracy!

Coordinating supply chains and pricing processes and tools is complex. It gets even more complicated if production scheduling needs to be optimized. The scenario for each part sold on each channel or location is straightforward:

- If demand based on current price > inventory = adjust replenishment to prevent stock outs

- If forecasted demand based on a planned price decrease > inventory = might need to reconsider pricing increases to prevent stock outs, or adjust ordering and replenishment to increase target inventory position

- If forecasted demand based on a planned price change < inventory = consider adjusting the replenishment plan to prevent inventory accumulation and/or lower price to increase demand

Of course these decisions are based on steady state demand, after seasonality and other demand fluctuations are accounted for. This can be done by considering an “inventory balancing period” with begin and end dates associated with calculated seasonal demand. This also allows promotional activities and other demand influences to be removed. Competitor behavior is difficult to predict, so for planning purposes calculated price elasticity represents demand changes as your price is adjusted relative to the market.

Business constraints should also be considered, but for the sake of simplicity, let’s consider the options based on current price vs two calculated price points, maximum profit price and inventory depletion price. Maximum profit price is the price where total profit is maximized based on price sensitivity, current price and cost. Inventory depletion price is the price at which demand exactly matches the current replenishment target inventory position. Here are the options where an item is underpriced or overpriced:

1. Item is underpriced, but the inventory depletion price is less than the maximum profit price = decide if depleting inventory is more important than lower profits, otherwise adjust replenishment to increase available inventory up to demand associated with maximum profit pricing

2. Item is underpriced, but the inventory depletion price exceeds the maximum profit price = decide if depleting inventory is more important than lower profits

3. Item is overpriced, but the inventory depletion price is lower than the maximum profit price = decide if depleting inventory and higher sales is more important than higher profits

4. Item is overpriced, but the inventory depletion price is higher than the maximum profit price = decide if depleting inventory is more important than higher profits, otherwise adjust replenishment to increase available inventory up to demand associated with the maximum profit pricing

A key part of the analysis is comparing the change in financial metrics moving from current price to recommended optimal price or inventory depletion price. It is also important to compare the difference between optimal and inventory depletion price to understand the financial impact of adjusting steady state inventory levels and the tradeoff between optimal price and adjusting inventory levels. Similar analysis can be done to determine the financial cost of burning off inventory.

I am ignoring the Use Cases where inventory depletion price is lower than current for an underpriced item and higher than an overpriced item. In these situations replenishment should be adjusted to minimize further loss of profits rather than adjust price to match demand with target inventory position. Of course this depends on confidence in calculated maximum profit and inventory depletion points, but making pricing and inventory decisions based on the best information you have is better than ignoring the information altogether. Confidence will improve over time as prices are adjusted and models gain accuracy and statistical confidence over time, one of the primary advantages of self-learning models.

Bottom line: Pricing is the largest influence on demand for many items. This leverage can steer demand to deplete inventory, maximize profits, or a combination of both. Efficient organizations can adjust replenishment to match inventory levels. The key is completing this and achieving desired financial outcomes like maximized profits, even as demand shifts over time with seasonality, changing market preferences, and other factors.

I am sure there are many people in my network who will point out what I missed! If you liked this article or think of something to add, please leave a comment or ask a question.

Shameless plug: Information about my company Prolific Virtue is here. One of our goals is to get simple, easy to understand pricing solutions in the hands of everyone so consider trying our solution Prolific Pricing here – all you need to provide is an email to register and begin using our pricing tools.

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