About Jeff Harrop

One and Done

Posted on June 3, 2026 by Jeff Harrop

Sometimes you get no second chance and it’s best to accept the gifts the world offers you. – Paolo Coelho

Special Buy! Hot Deal! While Supplies Last!

These are the items that are brought in for a limited time to drive sales, traffic and GMROI. They go by different names: One Time Buys, Promotional Items or Opportunity Buys. Sometimes they complement the core assortment, sometimes they seem to have no business being in the store at all. As a customer, they often leave you asking: “How the hell is anybody making money on this?”

They generally originate in the packed warehouse of a manufacturer or distributor who perhaps misjudged the market. They now have tons of stock that’s not moving and they need someone – anyone – who can take it off their hands (and their balance sheet) and clear some space. And the only way to clear out that much stock so quickly is to call up a retailer with the store network and infrastructure to take it all at once.

But they need to make it worth the retailer’s while to set the item up in their systems and utilize the space in their trucks, warehouses and stores to get it in the hands of consumers without (hopefully) being stuck with excess stock themselves. This usually culminates in an offer from the supplier: “Take it all (or a large chunk of it) off my hands now and I’ll charge you pennies on the dollar – but I’ll need the purchase order by Friday.”

Retail buyers receiving offers like these now have a decision to make. If they can set a selling price that will allow them to sell through it quickly, not cannibalize their core products too much, and turn a profit on it (factoring in the additional supply chain and administrative costs), then it’s a go. It’s basically a boost in their sales and GMROI numbers with limited risk. Not to mention the traffic these items can drive to the store, adding more incremental sales across the range.

Supply chain folks – while understanding that these products can be good for the business overall – are generally less enthused about figuring out how to push a basketball through a garden hose.

This is the part where well meaning people can make dealing with these items more difficult than it needs to be. We’re buying it once and never replenishing it again. We’re not trying to maintain an in stock target for them (running out is a cause for celebration, not concern). There’s really no point in developing forecasts and plans, so let’s just bypass the planning system altogether. Get them into the DC and then just push them out to the stores!

While it’s true that the purchase may not be planned in advance – they really sort of just drop into your lap – the newly purchased product still needs to get all the way into the customer’s shopping basket. Why “push it all out at once”, when there may be an opportunity to hold some back in the DC and allow the stores who are selling it faster to pull it? This can put all the cash into your hands faster overall and avoid obsolescence and further markdowns to clear it.

Most retailers who invest in planning systems don’t want to just use them to manage inventory balances. Significant value comes from being able to convert and roll up numbers from the elemental level to manage all of these key resources of the business (cash, labour and capacities) that are consumed to get products into customers’ hands. But this only works if the plans contain everything that will consume those resources – including the one time buy items.

Sales, transportation, capacity and space plans that don’t include these items will have large gaps in them that need extra effort, assumptions and “fudge factors” to fill in. Why wouldn’t you just include them in the plans in the first place? It’s not as arduous a task as you might think.

To begin with, these items will need to be set up with item numbers, supplier codes, pricing, costing, descriptions, UPCs and logistical attributes in various systems anyhow (ERP, WMS, POS, Online Store, etc).

Retailers using planning systems already have processes for setting up new items that can be used for any new one-time buy item:

Model the new item based on an existing item by copying and scaling sales history to calculate a forecast
Set a start selling date on the new item so that the forecast is zero until the item is expected to be on the shelf at the stores
Set a future dated minimum stock level for each store with an effective date on or before the start selling date – for a one time buy, this could be as simple as “everybody gets 1 pallet each to start”

Similarly, when an obsolete item is leaving the assortment, a final purchase date is set after which there will be no more replenishment from suppliers into the DCs. The planning system will then model the runout of stock from each DC based on planned outbound shipments to the stores, followed by the runout of stock in each stores based on sales to customers.

We generally think of the full product lifecycle as a period of months or years between introduction and discontinuation, but it doesn’t have to be. For a one-time buy item, you would just plan them both simultaneously – set it up as you would any new item, then apply a final purchase date equal to the day the one and only purchase order is due to land in the distribution centre. After that, allow the planning system to plan the flow from the DC into each store, adjusting the forecasts and plans as the sales materialize and updating the runout date for each store:

With these couple of extra steps (for which you have processes and procedures already), you can:

Actively manage the flow of goods from the DCs to the stores based on how each store is performing
Have an up-to-date view on how long it will take each store to sell through their one-time buy items
Manage your non-inventory resources to get the products from the receiving door of the DCs into customers’ hands as visibly and efficiently as possible

While “buy it and push it” might sound like a simple shortcut, it’s one that’s not really worth taking if you consider all of the benefits of planning. Plus, when you add up the additional manual work it requires, it may not wind up being a short cut at all.

Sources of Truth

Posted on April 1, 2026 by Jeff Harrop

Planning is bringing the future into the present so that you can do something about it now. – Alan Lakein

Most retailers have two sources of truth:

The data warehouse holds information about the past at the most granular level. It allows you to construct a complete picture of things that happened over the last several years at the lowest level of granularity:
- Sales of specific items at specific locations on specific days
- Stock movements between locations for specific items on specific days
- Stock levels of specific items at specific locations on specific days
The ERP system holds information about the present at the most granular level:
- Current information about items, locations and source/destination relationships
- The current on hand level for each item at each location right now
- Open stock transfers and purchase orders and their status (committed, shipped, received) right now

Of course, there is no source of truth for the future, because it hasn’t happened yet.

But what if there could be?

It’s true that the future is uncertain. But uncertainty isn’t an all or nothing proposition (regardless of what the “forecasts are always wrong, so why bother at all” crowd may say).

Here are 3 predictions of events that haven’t happened yet:

The sun will rise at 6:24am on August 12th, 2026 in Kitchener, Ontario, Canada – very certain.
My electric bill will be between $200 and $275 per month during the summer months – pretty certain.
It will rain for 4 hours on June 23rd, 2027 – not at all certain.

As a brief aside, Larry Smith – my first year Macroeconomics professor shared this sage (if tongue-in-cheek) advice in one of his first lectures of the semester (this lecture was 35 years ago, so this isn’t a direct quote, but it’s pretty close):

“For those of you who are looking to pursue a career in economics, there will inevitably come a time when someone will ask you to provide a forecast of something. The secret to being good at forecasting is to provide a specific magnitude or a specific timeline, but never both.”

Okay, back to the point I was making…

When it comes to supply chain planning in retail, there are a LOT of things that fall into the very certain (“we will be promoting this product at all stores for half price during the first week of September”) or pretty certain (“we think we’ll get a 60-70% sales uplift on this promotion based on past performance”) categories.

There is certainly enough there to construct a valid simulation of reality: a continuously recalibrated source of future truth – making full use of the past and present sources of truth – at the same level of granularity as the data warehouse, but with the ability to answer far more valuable questions:

What are sales expected to be for every item at every location and at what price for the next 12 months? Are we going to meet our sales plan?
How much stock are we expected to have in each item at each store and each DC tomorrow? Next month? A year from now?
How much of each item will the DC need to ship to each store each day? How much will be coming inbound? Do we have the capacity for that?
How much are we going to be purchasing each week for the next year? Do we have cash/financing set up to support that?

It’s like having a fully constructed data warehouse for your business where all of the dates are in the future instead of the past.

But getting to this point will require spending some time on business processes to make sure that you’re fully incorporating the “very certain” and “pretty certain” aspects of the future into the plan itself.

In practical terms, this means:

Plans are always complete and updated continuously – anything you currently know about the future (upcoming promotions, network flow changes, new products, etc.) goes into the plan today
When you’re in the realm of “pretty certain” (e.g. promotional uplift estimates, new item forecasts, impact of price changes, etc.), consensus on the inputs and assumptions among people with different viewpoints can serve to chip away some of the uncertainty and get everyone on the same page
Focusing your effort on the one truly independent variable (consumer demand) and let all of the supply movements flow from that based on the things that are largely known (stocking policies, constraints, lead times, etc.)

By shifting your mindset from “we need to order better” to “we need our plans to always reflect our most current view of the future at every level”, you can not just reduce out-of-stocks by 80% and increase turns by 40% or more, you can do it with greater operational and planner efficiency.

The Size of the Prize

Posted on February 4, 2026 by Jeff Harrop

An object in possession seldom retains the same charm that it had in pursuit. – Pliny the Younger (62AD – 114AD)

As with all other industries and disciplines, retail supply chain planning is about to be rocked to its core by new AI technologies. Or maybe it’s going to fail spectacularly. The answer is probably somewhere in the middle.

Well, maybe.

We’re still at an early stage where multiple experts (people with far more knowledge about AI than I do) can have diametrically opposed views of where the technology is headed and they’re all looking at the same information.

Personally, I (along with nearly everyone else) avoided buying Amazon stock in 1996 when they were just an online bookstore hemhorraging cash every quarter. My point is that I’m not a futurist or an expert in AI, so I won’t be weighing in on whether or how it will ultimately impact how supply chains are planned in the years to come.

But what I think we can do right now is try to determine what the potential size of the prize actually is in terms of business results to a typical retailer.

First, we need to set a baseline of what retailers can achieve without the use of AI technology. Continuous time-phased planning has been around in manufacturing and distribution for quite awhile, but it’s still a relatively new concept in retail. And here I’m not just talking about forecasting and replenishment, but truly modeling the current and future policies and constraints of the supply chain from the retail store to the manufacturing plant over a long term time horizon – we call it Flowcasting.

It’s been well documented for at least the last 30 years that retailers who don’t plan in an integrated fashion from the store shelf back to their supplier base achieve in-stock levels in the 92-93% range. Those same studies estimate that every 3% improvement in in-stock leads to a 1% increase in top line sales.

Through our work with numerous retailers over the last 3 decades, we have proven that in-stock can be sustainably increased from the 92% range into the 98% range while simultaneously improving inventory turns by 20-40% (depending on item velocity and minimum merchandising requirements in the stores). This can be done by following some proven principles and strategies from manufacturing and distribution (tailored to apply to a retail business), namely:

Create a forecast of true consumption for every item at every selling location
Calculate long term replenishment plans for every item at every stocking location and link plans up the chain (i.e. from stores to DCs to suppliers)
Keep the plans up-to-date with any known current or future external or internal impacts to demand or supply
Make sure that everyone (including suppliers) always has an up-to-date version of the plan so everyone is working to a single set of numbers

This is all standard, old school DRP/MRP stuff. No magic. No AI. And while technology (especially the ability to process large data volumes) is enabling these results, the shift in mindset on the part of the retailers is as important, if not more so:

If you know about something today that will happen in 3 months (e.g. a promotion, new product launch or store opening), get it into the plan today
Don’t keep the plans a secret – let everyone see the plans and assumptions that go into making them so that everyone can be aligned on how to execute them
Work by exception – let the plans tell you about potential problems that you need to start working on now before they become actual problems

This brings us back around to the actual size of the prize of AI in supply chain planning. The primary gap that needs to be closed in retail is the stubborn and pernicious 8% out-of-stock rate.

By applying process discipline, planning technology that enables it (without a single drop of AI) and connecting up-to-date plans up and down the supply chain, this gap can be reduced to 2%, while simultaneously making substantial improvements to inventory turns.

Even with highly advanced artificial intelligence that hasn’t even been developed yet, getting to 100% in-stock is a practical impossibility – with millions of item/locations in the retail supply chain, there is too much that can go wrong operationally outside the control of the planning function. So, at least as far as in-stock is concerned, the net incremental benefit above continuous planning is less than 2%.

Once the technology matures, there will undoubtedly be ancillary benefits of greater automation to planner productivity (hopefully not at the expense of accountability), but you don’t need sophisticated AI models to squeeze the vast majority of the juice from the lemon.

A lot can be achieved by just giving people the right processes, tools and a single plan that they can control and execute together.

What’s the Impact of Your Promotions?

Posted on December 3, 2025 by Jeff Harrop

It’s the little details that are vital. Little things make big things happen. – John Wooden

As a retailer, how important are promotions to your business?

Whenever we engage with a new retail client, this is one of the first questions we ask. Promotions – particularly short term price promotions – can have a profound impact on the supply chain (think about trying to shove a basketball through a garden hose) and pretty much always requires some significant thought around processes to plan and execute them properly.

More often than not, we’ll get an answer along the lines of “We do 30% of our business on promotion.”

How do they come up with this number?

Virtually all modern point-of-sale systems will flag a sale as promotional when it is being transacted, which makes things pretty simple: Sum up all of your sales where a promotional code has been affixed by the POS system, divide it by your total sales for the same time period and voila – you get a percentage you can recite to anyone who asks.

But does that actually mean “you do 30% of your business on promotion” or does it just mean that 30% of the sales you transact have a promotion identifier applied by the POS system?

If the overall goal of promotions is to drive additional sales and traffic, you can’t really measure them against that goal unless you know (or can reasonably estimate) a number of things, beyond just the sales that were recorded:

How many customers were going to buy promotional items at full price that week anyhow?

How many customers were going to buy promotional items at full price in future weeks but purchased decided to purchase earlier and/or in larger quantities to take advantage of the promotional price?
How many customers were going to buy a different brand at full price, but switched to the brand that was on sale?
How many customers were going to pay full price for a different brand, but switched to a promotional item instead?
How many sales did you miss because a number of stores ran out of stock before the promotion ended?
Etc.

The specific impact of each of these consumer behaviours can vary item by item and store by store. Even worse, none of this information is stored in your POS system (or anywhere else), so if that’s all you have to work with, it’s really tough to understand the true impact of promotions on your business.

But what if you had a process and a system at item/store level that could:

Identify promotions and other events in your sales history; and
Estimate and isolate the incremental impact of those events for the purpose of developing a baseline forecast?

This would give you a view – for every item at every store – of what your sales would have been in each week that was impacted by a promotion:

A graph of a graph

AI-generated content may be incorrect.

The methods for calculating “sales that would have been” will differ, but this type of sales history cleansing/segmentation is standard functionality for virtually all forecasting systems. Putting aside the “how”, the “what” gives you what you need to better estimate promotional impact:

A graph with lines and text

AI-generated content may be incorrect.

So now in addition to knowing that you sold 31 units at the promotional price, you also know:

The actual uplift in sales during the promotion week was 22 units – in other words, had the promotion not happened, you would have still sold 9 units at regular price that week.
This store ran out of stock 5 days into the promotion. Had that not happened the actual sales could have been 40 units.
Because of customer hoarding behaviour (or perhaps the stockout mentioned above persisted into the next week or two), your regular price sales for the next few weeks after the promotion declined by 11 additional units.
When a competing item was on promotion a few weeks later, this item was cannibalized to the tune of about 15 units.

This is the story for one particular item at one particular store and in sales units only – and that’s the whole point. When you plan in this way at the most granular level, you can gain insights at every level above it that can help you with planning future promotions, by understanding:

What was our true incremental sales gain from promotions?
Was our incremental sales gain constrained due to out-of-stocks during promotional periods? How do we factor this into our forecasts and stocking plans for future promotions?
How much did we sacrifice in regular price sales and what was the true incremental profit gain from our promotional activity?
Does the incremental profit gain reasonably offset the additional costs of promoting items (advertising, signage, store labour, logistics costs, etc.)?

Knowing that promotions are key to your business is one thing. But knowing their true impacts and tradeoffs to sales and profitability can really help you make better decisions that will squeeze maximum value from your promotional activity.

Just In Time… For What, Exactly?

Posted on October 6, 2025 by Jeff Harrop

I have noticed that the people who are late are often so much jollier than the people who have to wait for them. – E.V. Lucas

The time-phased, arrival based planning logic that underpins Flowcasting has frequently been described (sometimes disparagingly) as “pull-based, just in time”. Depending on your definition of “pull-based” and “just in time” (do any two people actually agree on what these terms mean?), there’s more truth to that than fiction.

The “pull-based” part is easy. The retail supply chain hasn’t finished its job until a customer has made a purchase. While it’s possible to encourage a stronger customer pull with promotional offers, pricing and markdowns, you can’t push unwanted stock into a customer’s shopping cart and force them to pay for it. This is true for every saleable item in every retail store.

The “just in time” part is what can sometimes make people (particularly buyers) a little queasy. The term evokes images of stock running almost to zero just before the perfectly executing supply chain delivers more stock. There seems to be a pervading fear that such approaches will cut inventory to the bone in a blind bid to increase stock turns at a all costs.

While it’s certainly possible to run your supply chain (including the stores) super lean, it’s definitely not necessary – nor recommended. A store with just enough stock to cover anticipated demand and variability for every item will look like it’s perpetually going out of business.

“Just in time” doesn’t mean “just enough to support sales”. It means just in time to prevent the stock level from dipping below a minimum floor that you decide.

Do you want to maximize turns with minimal safety stock? No problem!

Do you want to have a nice, full looking display with at least 5 facings, 3 deep on the shelf at all times? Go for it!

(Same item, same store, same sales forecast).

Do you want to augment the normal shelf stock with secondary promotional displays for a few weeks? Nobody’s stopping you!

Would you rather have a minimum of 4 weeks of supply in the store at all times? Sure! Why not?

Just in time isn’t about stock levels, it’s about stock flow. So long as you can articulate what minimum stock holding you require for each item/location and when (and can justify it to Finance), a proper just in time planning approach does what it’s told and flows in stock to ensure you never fall below that level.

Merchants and space planners rejoice and be glad! You’re not slaves to just in time planning. Just in time planning is a slave to your merchandising needs.

Order From Chaos

Posted on August 7, 2025 by Jeff Harrop

A schedule defends from chaos and whim. – Amy Dillart

Retail Systems Research recently surveyed 133 US retailers of various sizes ($250M+) and across 5 verticals on the subject of tariffs. The authors were trying to understand how retailers view the tariffs in the short and long term and how they are responding to them.

Some of the results were highly predictable – most are feeling the squeeze of trying not to alienate price conscious customers at a time when their cost of goods are increasing because of forces out of their control – but there were also some somewhat shocking surprises. A significant majority believe that in the long term, “the benefits from the current tariff policy will ultimately outweigh the short-term drawbacks to our business”. Those expected benefits, they believe, will flow from increased onshoring of manufacturing in the United States.

But there seems to be some inconsistency (cognitive dissonance?) at play, as the authors note:

“Most retailers excluding those selling fast moving consumer goods believe that robots will perform US-based manufacturing tasks. Yet they also believe that renewed manufacturing in the US will create a significant new job market. It is unclear to us how to reconcile those two opinion sets. It isclear retailers are all feeling quite positive about near-sourcing and ultimately benefits will outweigh the risks.

Again, it’s hard to reconcile these seemingly divergent opinions (remembering that most retailers don’t think they can survive even a year of tariff-driven retailing). It is emblematic of our country as a whole today: torn between the need for more self-sufficiency, yet unsure how to get there from here.”

I guess that’s chaos for you.

It’s a fascinating study and also a glimpse into the future for US consumers on how retailers are planning to respond to the tariffs.

They conclude with 7 recommendations for retailers that could be applied to chaos in any form (pandemics, natural disasters, financial crises, etc.). Six of those 7 recommendations are coded directly into the DNA of Flowcasting and – in our view – should be a “way of life” for retailers even in times of relative “calm” (or maybe the correct term is “normal background chaos” that always exists in retail, even if they’re not talking about it on CNN).

Acknowledge The Chaos

2025 has proven to be anything but normal, as an environment of wildly fluctuating tariffs has completely upended the relative stability retailers – and their supply partners – were expecting at the beginning of the year. The hard truth is that our industry is now trying to plan – what to buy,what to sell, how much demand there will be, how much supply will be needed – in an environment when planning is nearly impossible. Acknowledging this chaos is now the first step on the journey, as all indicators point to this being the “new normal” for the foreseeable future.

In Flowcasting speak, we call this “documenting your assumptions”. When you don’t know exactly what will happen in the future (and who really does?), you need to gain consensus on your best guess and then anchor your plans on that. As time unfolds, the assumptions you made may not hold water (more on that below), but at any point in time, everyone knows the thought process that was driving the plans.

Embrace ‘Sense And Respond’

The plan may be out the window, but that doesn’t mean a new plan shouldn’t take its place. We advise retailers to use the data available and new analytics to sense and respond to changes in market conditions as quickly as they possibly can. Just as it was during the pandemic, this is a time to get creative. Retailers have shown – time and again – that when backed into a corner, they are more than capable of adapting.

Throwing plans out the window and creating a new one to take its place is what Flowcasting is really all about. For every item at every location every day. While retailers writ large have shown that “they are more than capable of adapting”, those with fully a fully connected planning process from the store shelf back to the supplier can adapt far more quickly, accurately and efficiently.

Forecast Continuously And Adjust

Forecasts need to be updated in-season as the selling period unfolds to make short-term adjustments. This capability is empowered by new data (customer, product, competitor, and market) and the analytical tools that can turn those data into insights.

This recommendation goes hand-in-hand with “sense and respond”. With Flowcasting, forecasts are updated daily for every item at every selling location with current sales. As far as “turning those data into insights” goes, the continuously updated demand forecasts drive a fully integrated end-to-end model of the supply chain that updates the product flow plans from the store shelf right back to the supplier, also on a daily basis. What could be better than that?

Recognize That Scenario Planning / Predictive Modeling Is Vital

Few forward-thinkers would deny that the world will become more unpredictable with time. Weather events, social norms, wild swings in the geo-political world – all happen faster and less predictably than at any time in the recent past. Retail Winners view their ability to use predictive modeling techniques as key to helping them to react much more quickly to supply chain disruptions and sudden shifts in demand.

Digital transformation and the technologies it employs makes it possible for retailers to predict all kinds of unforeseeable patterns before they occur – to model future states – and react to them faster once they do. This has moved from being merely a winning behavior to becoming essential to survival.

With a realistic model of the supply chain constructed in a single system, scenario modeling is very quick and easy to do (i.e. “plug in some new assumptions and see what happens”). Not only can different demand scenarios be modeled to determine the impact on sales, costs and service, but you can also game out various supply side strategies that can be deployed in response. Once you have a complete plan that looks like it will work, you can commit the changes and start executing to it across the board. If it starts to look like it’s not going to work, you can change it.

Trust That Pricing Solutions Can Help – Even In Pricing Chaos

Consumers continually cite price as a primary value attribute, and retailers continually tell us price is something they need to get right. New technologies can bring advancements to pricing right now – not in some distant future. RSR’s take is that retailers simply cannot afford to overlook this opportunity. Price optimization solutions have improved to the point that changes as granular as SKU/location can be recommended daily based on dynamic demand and inventory availability.

Whether retailers want to be that granular and fluid is another matter, but (especially with the continued adoption of electronic shelf label, or ESL, technology in stores), retailers could be better able to maintain profitability even in the face of wildly fluctuating cost-of-goods, by taking advantageof what new pricing solutions have to offer.

While this recommendation is not in the direct purview of Flowcasting (pricing is taken as an input and the model does what it’s told), current and planned changes to pricing can be fed in at any level (right down to item/store/day if desired), forecasts can be updated at any level and the impact to the financials can be rolled up from there.

Maintain Flexibility At All Costs

The COVID-19 pandemic taught a great many lessons to retailers. The paramount need-to-know what inventory you have – and where – was just the beginning. How quickly a brand can change its course of action to deliver the right products to where they are needed very quickly is a lessonin the importance of flexibility that cannot be forgotten without creating risks to business survival.

Flowcasting allows not just the modeling of your supply chain as it exists today, but future dated modeling of planned changes to your demand picture, network flows, stocking policies, etc. right down to item/location/day level. And once you’ve modeled it, the system automatically executes the product movements at the right time.

Keep Every Eye Possible On The Supply Chain

The ability to monitor the supply chain in real time and react as necessary, using digital twin technologies to evaluate disruption scenarios and prepare supply chain to minimize financial impact, and the ability to enable “real time inventory management/visibility” are all top-of-mind capabilities for retailers.

Unlike standard computer assisted ordering approaches that only evaluate whether or not it’s time to request more stock on specific ordering days, Flowcasting recalculates demand and supply plans for every item at every location every day. With a complete model of the entire supply chain in a single system, it’s the ultimate digital twin that always has its eyes open.

It would be terrific if we could precisely predict the future, but that’s not possible even in times of relative stability. To the extent that you can come closer to this goal by collecting more information and improving your assumptions, by all means have at it.

But experience has taught us that the real secret to achieving maximum customer service with minimum inventory is not so much accurate forecasting, but continuous replanning.

Shaping the Plan to Your Will

Posted on June 4, 2025 by Jeff Harrop

I am a man of fixed and unbending principles, the first of which is to be flexible at all times. – Everett Mckinley Dirkson

As a retailer, if you can accurately forecast the impact of your promotions – down to item/store level – within a narrow range, then everything will be fine.

Umm, okay, that sounds great but what if – hypothetically speaking – you’re not always able to do that? Then what?

Flowcasting has been fairly accurately described as a demand driven supply chain planning approach, with “demand” in this context referring solely to pure demand from consumers at the shelf.

In order for Flowcasting to work properly, the forecast of future demand at each item/store must be representative of what you expect to sell in every planned week in the future. While the starting point for the forecast can be derived mathematically by detecting patterns in history, it needs to be augmented when you know something about future consumer demand that will be different from the past (sometimes referred to as “demand shaping”). In this case, you know that you’re going to advertise a price drop to your customers in Week 9:

In the example above for an item at a store, we expect to sell 64 units on the promotion. This store needs to maintain 20 units of minimum stock at all times to keep the shelf display looking presentable. Flowcasting logic ensures that the Projected On Hand will never fall below that Minimum Stock in any future week, so as a result, the high expected promotional demand in Week 9 triggers 66 units to arrive at the beginning of that week (all requirements rounded up to shippable packs of 6 units). With a 1 week lead time, that 66 units is seen by the servicing DC as a shipment that will be made to that store in Week 8.

We’re only looking at a single store here and there are a variety of ways to have the promo uplift applied (top-down based on proportional contribution to past total sales, promo sales or baseline forecast, elasticity curves, machine learning based approaches, etc.). The key point here is that demand must be appropriately shaped and represent what you actually expect to sell.

What we have here is a really good plan… If you’re confident in your promotional forecast and if you’re just going to put a promo tag on the home location. For a lot of products (e.g. those that you’ve promoted frequently at the same price with no additional merchandising support), this might be just fine and dandy.

But what if you need product to be in the store earlier or in greater quantities than required just to support expected sales? This could be to support the set up of off-shelf displays or cover for upside forecast risk (particularly if shipments to the store are relatively infrequent and there may not be enough time to do a “mid-course correction” once the promotion starts).

This need is sometimes referred to as “push/pull” or “decoupling” and it can be a real challenge, especially when your supply chain is… well… decoupled.

Flowcasting is uniquely capable of solving this problem quickly, precisely and well in advance so that everyone (store operations personnel, support office planners, buyers and suppliers) can see what’s going to happen.

Because Flowcasting connects the entire supply chain from the consumer to the supplier – it doesn’t support “decoupling” – it completely invalidates it.

For example, suppose that the item we planned earlier will be supported by an off-location display of 30 units in addition to the 20 units required as a minimum on the shelf. Furthermore, the stores need to have sufficient stock a week ahead of time to organize their merchandising teams to set up the display.

In Flowcasting, this is executed as a simple, future dated temporary change to the minimum stock:

Instead of stock arriving just in time to support sales, a large shipment to support the additional display will arrive the prior week, while the additional stock to support the sales uplift will arrive later.

Okay, but what if you’ve never promoted this item at this price point before? The forecast is your best unbiased guess at what’s going to happen, but you would rather have additional stock at the store than risk running out.

Here, we’ve set our minimum stock during the promotion week to ensure that we’re covered if we sell double what we expect.

What if this store can get multiple shipments during the promotional week? You can instead apply a safety stock uplift to the distribution centre plan so that the stock is positioned there to quickly refill stores that are selling through it more quickly, while not overloading the stores that aren’t.

Or you can split the difference by adding some of the additional safety stock to the stores and some to the DCs. Or… you get the idea. All nodes are planned and all nodes are connected, so the effect of changing the shape of the supply plan is precise and the impact on all nodes is transparent.

And by planning in this fashion (shaping the supply plan separately and independently from shaping the demand), there is an additional advantage over pushing stock out via allocation: continuous replanning. The planned shipments and arrivals will be recalculated every day as sales and inventory movements are realized between now and when the promotion starts. And everybody sees how the plan is shifting over time at every location, right back to the supplier.

While there are other methods for shaping the flow plan (temporarily bypassing nodes with planned network flow changes, days of supply/safety time, etc.), simply having separate levers for demand shaping and supply plan shaping is a very effective way to plan not just promotions, but any other scenario where “decoupling and pushing” would be used outside of a Flowcasting context:

Cannibalization and halo effects on items that compete with or complement a promoted item
Planning for the initial pipeline and shelf filling, followed by ongoing replenishment for a new item
Pre-building stock ahead of a seasonal or holiday peak

Plan the execution, then execute the plan.

What could be simpler?

Empty Calories

Posted on April 2, 2025 by Jeff Harrop

There is not any memory with less satisfaction than the memory of some temptation we resisted. – James Branch Cabell (1879-1958)

What are my current stock levels? What’s the status of my inbound orders? How were the weekend sales for my products?

A great deal of effort has been spent over the last 2 decades to provide this information to planners and decision makers in near real time. But how useful is it, really?

We like to call this the “salt, sugar and fat” of supply chain planning. It’s extremely satisfying to get answers to these questions in the moment, but the satiation wears off quickly and you find yourself asking the same questions a few days later.

These types of supply chain visibility metrics are merely a glimpse in the rearview mirror. The myriad activities that give rise to a particular inventory level, a change to an order status or a weekend sales result have already happened and have been happening for days, weeks or even months before the question was even asked.

It’s like sitting at the gate and your airline announces a departure delay. You would rather have that information than not, but if that’s all the information you get, you have no control over the outcome. All you know is that you won’t be getting to your destination on time.

Now, suppose that you’re a savvy traveller. Hours before you even leave for the airport, you check the tail number for the inbound flight. Then you check the origin city of that flight and a massive storm is rolling through right around the time it’s supposed to depart, virtually guaranteeing a significant delay.

What are you going to do? Try to get booked on a different airline whose inbound aircraft is not coming from the city that’s about to get pummelled? Extend your hotel stay for another night because there’s no way you’ll be getting out at a reasonable time? Rent a car and just make it a road trip instead? Or just suck it up and leave on your scheduled flight, even though you know you’re going to be significantly delayed.

Any of those options may be acceptable, depending on your needs and constraints (e.g. cost, how urgently you need to get to your destination, whether or not the distance is reasonably driveable). But you only have one option available if you didn’t see the problem coming and only learned about it when you were sitting at the gate.

The point here is that knowing where things currently sit is certainly useful, but nowhere near as useful as being able to anticipate what things will be like in the future. Constantly checking in on up-to-the-minute information about the very recent past may give you a sense of control, but in reality, you’re just sitting in the back seat bingeing on cheeseburgers and donuts.

In a supply chain context, focusing too much on “real time current” information can lead to false conclusions and bad decisions (or non-decisions).

You look at your current DC and store stock levels and everything looks nice and healthy, so you breathe a sigh of relief and move on to the next item. But a promotion is scheduled in 2 weeks that’s going to virtually wipe you out. And your lead time from the supplier is 4 weeks. This is an example of something that is a big problem, but it doesn’t look like a problem in the current data. The cost is lost sales that could have been avoided.

You move on to another item and you see that 30% of your stores are out of stock. So, you panic. You spend the morning trying to figure out how can this be? What happened? And you have a bunch of higher-ups (who are looking at the same “here and now” data that you are) asking the same questions. Meanwhile, an order was just triggered with the supplier that covers the shortfalls and is due to arrive in a few days. Within a week or so, all of the stores will be back in stock. This is an example of something that looks like a big problem in the current data, but really isn’t much of a problem at all. The cost is stress and lost productivity trying to solve a problem that has already been automatically solved.

Subsisting on a diet consisting mainly of salt, sugar and fat is not good for one’s long term health. So, how do you kick the habit?

Like the savvy air traveller, you need to give yourself a window into the future to know all of your options and make the best decisions in advance.

Properly cooked, an end-to-end planning process that is designed to always maintain a valid simulation of reality is a very tasty and nutritious vegetable.

Are You Sure You Want High In-Stock?

Posted on February 5, 2025 by Jeff Harrop

All exact science is dominated by the idea of approximation. – Bertrand Russell (1872-1970)

Okay, so that title might seem a bit “clickbait-y” and even a little dumb without some context, so bear with me here.

Before we get started, this piece is not about optimizing inventory investment by paring back inventory (and risking out of stocks) on long tail items “for the greater good” or any other such nonsense.

If you’re in the retail business in 2025, then you’re competing with Amazon at least to some degree. Those long tail items are probably as important to your long term success as a business than the so-called “bread and butter” fast sellers.

If holding stock on those long tail items gives you heartburn, then you’re better off increasing the selling price to offset the carrying cost than trimming your inventory. Customers will pay a premium if they know you’re the only game in town (or at least the most reliable game in town) to get those hard-to-find items.

Now, back to the topic at hand.

If you read the title of this piece and thought to yourself “What a dumb question!”, I’d wager that you were probably conflating the terms “in-stock” and “on shelf availability”.

What’s the difference? Customers don’t care that you have available stock somewhere within the 4 walls of the store. They want it on the shelf.

While it’s true that stock can’t be on the shelf if it’s not in the store in the first place, there are times when putting additional inventory in the store to boost your in-stock metric can actually harm on shelf availability – and sales.

Consider a simple example for a particular item where the shelf capacity for the item is 10 units. The shelf is completely full and the store is currently holding an additional 20 units in inventory in the back room or some other overflow location.

A couple of weeks go by. The 10 units of shelf stock has sold and the selling location is now empty. For a few days, either nobody notices the hole, the stock has been misplaced or is in a difficult to access overflow location within the store.

What will the replenishment system do? Probably nothing, because there is still plenty of stock in the store to sell. How does the in-stock report look for this item? Fantastic! But you’re losing sales.

In other words, boosting inventory levels in the store will definitely improve your in-stock metric, but if it’s done to excess, inventory can actually harm sales.

One problem we have is that in-stock is relatively easy to reliably measure, while on shelf availability is not. So we are forced to use in-stock as our proxy measure for customer service, when that’s not always the case.

So getting back to the original question: Are you really sure you want high in-stock?

The answer is yes – so long as you’re actively doing everything you can to effectively make in-stock a reliable proxy for on shelf availability:

Keeping your store level inventory accurate
Developing and maintaining accurate planograms (and compliance to those planograms in store)
Triangulating your planograms with stocking policies and pack sizes to ensure that inbound stock can flow directly from the receiving bay to the shelf

We Don’t Need a Ferrari

Posted on December 4, 2024 by Jeff Harrop

Necessity never made a good bargain. – Benjamin Franklin (1706-1790)

When a retailer seriously embarks on an effort to completely reshape how they plan the flow of goods from supplier to shelf, the discussion inevitably turns to what software they will need to do the job. (And ideally, this isn’t Step 1 of the process).

As the time approaches to evaluate software vendors, someone in company leadership is bound to utter the phrase “We don’t need a Ferrari”. After that, everyone in the room will nod their heads sagely in agreement. You can almost set your watch by it.

The message they’re trying to send is “We don’t need unnecessary sophistication and we don’t want to spend a ridiculous amount of money. We just need to get the basics right.”

I believe the intention is correct. You don’t want the design and implementation team to go off on a wild search for the most sophisticated system they can find – whether or not it’s proven or even necessary. But the advice may not be as useful as you think.

People who are tasked with transforming supply chain planning generally don’t need to be constrained or reined in. They need to be led. By the time you get to this point, you should already have assembled a team with strong convictions and a bias toward pragmatism – they won’t run around chasing shiny objects. Sometimes they will need leadership to be led by them.

Using well-meaning platitudes like “we don’t need a Ferrari” doesn’t really clarify anything and could potentially lead them down the road of picking a simplistic system over a simple one.

The team needs to understand time-tested and proven planning principles, what the true requirements of the organization are (including taking into account future strategic direction) and what results they are expected to deliver.

A system with a simple data structure, easy navigation and limited options that doesn’t adhere to solid planning principles and doesn’t meet the requirements will not deliver results.

Just because some functionality may be more complex or sophisticated than what you have today, that doesn’t make it “too fancy”, unless the mandate is to implement a new system and process that does the same thing you’ve always done (with the same results). Not all sophistication is unnecessary.

Just because people will need to acquire more skills – some of which may be difficult to learn – doesn’t mean that the system or process is “too complicated”.

No, you do not need a Ferrari – because nobody “needs” a Ferrari.

But there is a wide range of options between a Ferrari and a tricycle. Your requirements need to dictate whether you need a Corolla, a minivan or a pickup truck.

Don’t choose a tricycle just because it’s the farthest option away from a Ferrari. A simplistic system that doesn’t meet requirements makes the implementation just as complicated as an over-engineered system that you don’t need.