Learning to love beer

“Education is the most powerful weapon you can use to change the world.”

Nelson Mandela

If you’re like me, and most people for that matter, you love a nice ice-cold beer.

Think back, if you can, to the first time you tasted beer. What’d ya think? Probably didn’t really like it at first and it probably took time to enjoy the taste.

Driving change is a lot like getting comfortable with the taste of beer. It takes time. And repetition.

I recently read a great new book about change, called “The Human Element”, which outlined an interesting way to look at change. In summary, the book beautifully outlines the concept of fuel vs friction.

When it comes to change, most people focus almost all their energy on adding fuel to help sell the change – usually in the form of benefits, features, examples, and case studies, etc. However, as the authors point out, people are generally comfortable with and predisposed to the status quo and, therefore, at least as much effort should be spent on reducing friction – or why people naturally resist change.

One of the core strategies outlined is to acclimate the idea. Acclimate the idea through repetition and repeated exposure, which gives people time to think about, question and, over time, internalize the change. Much like the taste of beer, the sooner people are exposed to the change, the better.

It’s an idea and concept that we wholeheartedly agree with and is foundational to our approach to helping companies embrace, implement, and internalize Flowcasting. We expose people to the taste of Flowcasting through an early, ongoing, and repeated education program.

The education program is designed to help the organization understand and talk themselves into the changes required to enable the Flowcasting process to be instilled – from Executive Leadership throughout the extended organization, including merchandise suppliers since they will also change their thinking and processes to support the new ways of working. The goal of the education program is to not only disseminate knowledge but also, importantly, to build commitment and ownership since the change is driven by the executive team with an executive level of commitment.

Questions are at the heart of the education program and when we can, we always try to have clients embrace and deliver the process education through a model we call cascade education. The model works as follows…

The design team builds and records an educational webinar that explains the new process design and demonstrates it using a series of examples, including the fundamental principles of the process. The cascade works like this: The CEO reviews the online educational course and then requests that their direct reports do the same.

Once complete, the CEO would then lead a session (supported by the design team) with their direct reports, where a series of questions would be asked and discussed – ensuring not only a healthy dialogue ensued, but also, importantly, new questions would emerge that would be answered and potentially added to the list.

At the end of the session, the project team would revise the list of questions and the CEO would outline the expectation of their direct reports; each direct report would be responsible for ensuring their teams took the online course and, more importantly, attended a facilitated session (led by each direct report) where the questions would be discussed, and answers and opinions documented. The cascade would continue down the company hierarchy until everyone had taken the education and attended a principles-and-questions-based session to help people understand, begin to convince themselves and build commitment to the change.

The cascade model of education helps increase understanding of the change and reduce change reactance because the foundation of the approach is based on questions – some are asked but most are surfaced and answered by peers, helping people persuade themselves. Instead of the project team always telling, people are asking, listening, learning, and changing their thinking.

Education does not stop with the initial cascade. Additional sessions are built, tailored to specific teams and business scenarios. They are delivered, refined, and used to help people get comfortable with the changes needed throughout the extended organization, including all merchandise suppliers – which, given the number of suppliers a retail partners with, often requires hundreds of educational sessions to help them prepare and embrace the new ways of working.

Acclimate the idea. Early, often, and ongoing.

It works for giving you the time needed to love the taste of beer.

It’s also foundational for instilling change.

The Veil Has Been Lifted

You never know who’s swimming naked until the tide goes out. – Warren Buffett

Up until a couple of years ago, growth in online sales has been relatively slow and steady overall, with click & collect being the fastest growing channel. This put brick & mortar retailers somewhat back in the driver’s seat versus the pure online players like Amazon.

While brick & mortar retailers have struggled with execution in their online businesses, it represented a relatively small fraction of their sales. Most of their revenue came from foot traffic in their stores and retailers made steady progress investing in and nurturing their online businesses, with plans to grow those channels gradually over many years.

The COVID-19 pandemic changed all of that. Different retailers were affected in different ways depending on what they sell and where they do business, but many retailers needed to shift to nearly 100% online fulfillment for an extended period of time virtually overnight.

According to McKinsey, e-commerce experienced 10 years’ worth of growth in 90 days at the onset of the pandemic.



Responding to such a massive, unforeseen event in such a short period of time caused unavoidable stress in terms of store operations, staffing and variability in demand and supply, but make no mistake – a great deal of the pain was self inflicted.

You see, for years (decades really), customers have been subsidizing retailers for their poor stock management. When a customer in the aisle finds a gap where the product they wanted should be, about one third of the time the retailer loses the sale. But two thirds of the time, a customer will either switch to a similar product that is in stock or come back and buy it later, preserving the sale for the retailer.

This behaviour has been well documented in numerous studies on retail out-of-stocks, but it was all too easy for retailers to tell themselves “Yes, well maybe those retailers who participated in the studies angered their customers and lost sales, but not us. We’re special.”

Without the ability to definitively capture the absence of a sale that would have otherwise occurred in transaction history, many retailers could console themselves in the belief that the findings of those studies were academic and theoretical – the problem was surely not that bad.

Then the pandemic hit and many retailers were forced to conduct virtually all of their business online. And they got caught with their pants fully down.

The standard approach for fulfilling a click & collect order goes something like this:

  • A customer submits an online order for pickup at a store of his/her choosing
  • A check is performed against the store’s inventory balance to make sure that there is sufficient stock at the selected store to fill it
  • If sufficient stock exists, the order is assigned to the store for picking
  • The store picks the order and the customer is notified when they can pick it up

Makes perfect sense, but it only works if the stock records are reasonably accurate and the store knows where the stock is.

Based on discussions with our clients who routinely measured their online order fill rate (with reason codes for failures) during the pandemic, an employee in the store who is given a pick list (that has already been checked against the store stock balance before being issued) runs into an empty shelf up to 20% of the time when they attempt to pick the order.

(Sidebar: There REALLY needs to be a formal study on this)

To be clear, this was happening before the pandemic hit, but when online sales only represent 5-10% of your overall business, it’s easier to just sweep it under the rug and wait for it to become more pressing before doing anything about it. It becomes significantly more problematic when your stores are dealing with nearly 100% online sales volume for weeks or months at a time.

So, given that; a) an online customer isn’t in the store to make an “in the moment” decision to bail you out and; b) it’s not possible to undo years of neglect with regard to store stock management in a few days, what choices are left?

Actually, there are several. From a cost and customer service standpoint, none of them are good:

  • Take a margin hit by automatically substituting a more expensive version of what the customer ordered (if it’s in stock) in the hopes that the customer will appreciate it (which they may not)
  • Waste more of your time (and your customer’s) contacting them to find out if they really really wanted the item or if they would be willing to take a substitute.
  • Delay the order and/or incur significant additional cost having the out-of-stock item(s) rush delivered from the DC or another store who does have the out-of-stock item on hand.
  • Cancel the customer’s order altogether after exhaustively searching for the item(s) and coming up empty.

Hell, maybe the pandemic (or something like it) won’t repeat itself anytime soon and we can all go back to business as usual and deal with store stock management “at some later date”.

But what would be the downside of tackling it now?

Keeping it small

“I am a horse for single harness, not cut out for tandem or teamwork.”

– Albert Einstein

It’s early March 1975 and a loner saunters into a dungy and dark garage with a group of folks who have the audacity to call themselves the Homebrew Computer Club. The mission of this group of misfits: make a personal computer that is accessible to the masses.

Steve, a 24-year-old with long hair and a brown beard is an extremely shy introvert but is insatiably intrigued by the idea. He sits and listens. Doesn’t speak or ask a single question. He would continue to attend the Homebrew sessions, but rarely contribute.

Instead, he gets to work – alone. He arrives very early most days at work to learn and ponder – reading engineering magazines and books, studying the latest chip manuals, and thinking about a possible design. After work he’d hurry home, whip up a quick TV-dinner and then head back to his trusty cubicle, where he’d work late into the night. He’d describe this period of solitude, deep work and early morning California sunrises as “the biggest high ever”.

On June 29, 1975, around 10pm, Steve Wozniak would finish his initial prototype. He punched a few keys on the keyboard and voila – letters would appear on the screen. It was a breakthrough moment and he had built the world’s first personal computer – alone.

Fast forward 30 years or so, to the crisp, beautiful and serene landscape near Burlington, Vermont. Another engineer, Darryl, would be working on a solution for a problem that had perplexed supply chain planning technologists for quite some time – how to forecast and plan slow selling items in retail.

A few years earlier Darryl, and his long-time colleague Andre, would become frustrated in trying to convince supply chain planning software providers that they should build a store-level DRP solution (what we now call Flowcasting). Most ignored them, or worse, believed that could use a solution designed for manufacturing and distribution for retail. Eventually, one fateful day, they’d both say, “fuck it, let’s build something ourselves”.

Darryl, like Woz, would get to work – laser focused on being able to scale a planning system to retail volumes and developing a solution for planning slow selling items. Using actual data from a handful of retail clients, he’d test several ideas, refining and adjusting until eventually he’d bring forth an elegant, simple, and intuitive solution.

His breakthrough was achieved largely by working alone, just like Woz.

The solution for planning slow sellers is used by lots of retailers around the world to properly plan these type of items, including two of our Canadian retail clients.

Have you ever wondered how Apple has been able to bring forth a series of revolutionary products of elegant design and simplicity?

By keeping it small, that’s how.

Jony Ive was the Chief Designer at Apple and both he and Steve Jobs credit the fact that the iPhone, iPad, iPod and iTunes were breakthrough products because they were developed by very small teams.

According to them, a small, laser-focused team drives the innovation and then, as they share the design with others, they get good at “saying no to a thousand things” – to quote Jobs. Apple instinctively knows that every additional person added to the party brings more input and, very often, more noise.

For anyone working on projects and/or trying to design better ways, there’s some deep insight to learn from these stories. That is – small is not only beautiful, but generally produces better designs, implementations, and results.

So, to improve your odds of success, here’s some simple and practical advice that I always try to adhere to in any project I’m working on or leading:

  1. Reduce the number of meetings
  2. Reduce the number of participants in meetings
  3. Keep teams as small as possible

It’s a philosophy that’s worked well for Jobs, Ive, Bezos, Landvater and Doherty and I think it’ll work well for you too.

Orders, Allocations and Cursive Writing

When a subject becomes totally obsolete, we make it a required course. – Peter Drucker (1909-2005)

From third grade through to about the sixth, all of my classrooms had a banner posted above the front chalkboards (for those of you who don’t know what chalkboards are, you can Google it), showing the formation of all the letters of the alphabet – both upper  and lower case – in cursive form.

We all used special notebooks with 3 horizontal lines per row to guide you in making your cursive letters with the correct height and shape.

For 40  minutes or so every day, we’d practice. First an entire line of As (both upper and lower). Then Bs, then Cs and so on. After a couple weeks, we’d move on to writing whole words and sentences by joining different letters together in just the right way.

Being a lefty, I finished every class with the heel of my left hand completely coated in dark grey pencil lead. It was all worth it though, because it was a necessary skill to learn. Once mastered, cursive was a far faster and more efficient way of writing than using individually printed letters.

My mom was recently shocked and disappointed to learn that none of my 3 kids (now 22, 19 and 16) could write cursive.

My response?

Who cares! None of them can shoe a horse or start a fire with sticks either, but I think they’ll be just fine. Hell, for them, email is considered obsolete technology.

Truth be told – in spite of all the instruction and practice – I’m not sure that I could write five cursive sentences if you put a gun to my head. I type 60 words a minute on a keyboard, though.

Why do people cling so nostalgically to demonstrably inferior methods that they just happen to find more familiar?

That’s the thought that crosses my mind whenever I talk to retailers on the topic of allocating and ordering stock. Some think it’s the bee’s knees, the cat’s pyjamas and the elephant’s adenoids rolled into one.

Over time, the methods for determining which store gets which percentage of available stock become more sophisticated. Historical sales, current inventory levels, safety stocks, on order quantities and the price of Bitcoin are all factored in to make sure that stock is pushed out of the DC and each store gets the perfect allocation for each SKU.

But it’s still nothing more than a blunt instrument. Like sticking with cursive writing, but using a calligraphy pen instead of a number 2 pencil.

The most important factor in determining how much of any given item each store needs at any given time is the anticipated demand from customers for that item at that store. If you focused your energy on that one problem (forecasting customer demand), then simple netting logic can figure out the rest, including what needs to be in the DCs to support the demand in the first place. Ordering stock becomes a menial administrative activity unworthy of a human being’s time or attention.

Forecasts are by no means perfect, but the need to have stock positioned in anticipation of your customers’ arrival still exists and is the primary value a brick-and-mortar retailer gives to the world.

If you build a process around the ultimate goal of constantly learning what makes your customers tick, you will only get better at it.

And leave that number 2 pencil behind once and for all.

Compliments from a CEO

It’s always nice and also encouraging to hear positive comments from a retail CEO about Flowcasting and supply chain management in general. Below are some nice compliments from Ken Larson, President & CEO of Princess Auto Ltd, about Flowcasting, supply chain and the team (both internal and external) that helped make it happen. Thanks for the kind words Ken!

Working backwards

You’d likely agree that Amazon is a very innovative company.  AWS, Prime, Kindle, One-click-shopping are examples of innovations they’ve delivered through a process called Working Backwards.  Working Backwards is a systemic way to surface and vet ideas that sometimes lead to new products or services.  The key tenant of the approach is to begin by defining the product’s (or service) arrival, and then work backwards from that point until the teams achieve clarity of thought around what they will deliver.  

The main tool used to accomplish this clarity of thought is the PR/FAQ document – short for Press Release / Frequently Asked Questions.  The document is written from the perspective of the customer and is dated into the future, when they believe the innovation will arrive in the marketplace.  What’s simple, yet brilliant, about this approach is that it keeps teams focused on delivering something significant, valuable and meaningful to customers – rather than many approaches that are essentially based on the idea of incrementing-your-way-to-greatness.

You may not know, but Flowcasting is also based on the concept of Working Backwards.

Loyal disciples understand that the Flowcasting process starts with a forecast of consumer demand, by product and selling location (e.g., store, etc.).  Conceptually, what’s a forecast of consumer demand?  It’s when and where the customer wants to acquire the product – i.e., when and where it needs to arrive in their hands.

Flowcasting integrates the supply chain from this forecast of consumer demand by working backwards using an approach called arrival based planning.  For any product at any location, arrival based planning calculates planned shipments of when and how much inventory needs to arrive – scheduling a shipment so that the arrival date and quantity ensures the projected inventory doesn’t drop below safety stock.  

The basic logic is simple:

For each item/location:
1. Figure out what you expect to sell (or calculate what you’ll ship) 
2. Figure out what you have and what your constraints are
3. Figure out when you will need more product to arrive
4. Use the arrival based plan to figure out when you need to ship

The concept of planned shipments and arrival based planning is foreign to most retail demand and supply planners. After we do an educational session with planners, we often break people into teams and ask them to calculate a shipment based plan, using arrival based logic, with an example something like this:

Without exception, every retail client we’ve worked with struggles with this simple ask. Everyone has been so conditioned to focus on “ordering” that they struggle to understand that ordering (or committing the planned shipment) is the last decision, not the first. They are focused on “do we need to order” in week 1, rather than planning arrivals and the corresponding ship dates (i.e., planned shipments) first. 

Planned shipments are the foundational construct of Flowcasting and how the process integrates the retail supply chain to ensure the fundamental principle is achieved – that is, a valid simulation of reality.  Every planned shipment consists of an arrival date (when the product will arrive at the destination) and a ship date (when the product will ship from the supplying location).

Flowcasting plans shipments over the entire planning horizon and shares these projections with suppliers and other stakeholders in order to help them plan and improve productivity.  For suppliers we often refer to what is shared with them as a supplier schedule – that is, the projection of planned quantities and their associated ship dates by product and origin/destination.  

Ship dates are the key element to anchor the supplier schedule on.  That’s because ship dates are very specific from a supply chain and work perspective.  It’s when the inventory needs to be available and also when transportation needs to be scheduled to initiate the delivery.

The supplier schedule is, in most cases, the culmination of Working Backwards for a retailer who is using Flowcasting.  From the forecast of consumer demand, we work backwards to calculate when product needs to arrive and ship, through the entire distribution network, right back to when the factory needs to ship the product – integrating the entire supply chain via a series of dependent, cascaded planned shipments.

When you first hear the phrase Working Backwards it sounds like a dumb idea and implies you’re heading in the wrong direction.  Turns out, it’s been a proven and brilliant way to drive innovation.  

It also turns out to be the best way to plan inventory flows for the retail supply chain.

The Arrival Based Plan
For those students, here is the arrival based plan for the example outlined above:

What’s important to understand is that the planned arrivals that are calculated above would be the same, regardless of supply source.  They indicate the quantity and timing of a shipments arrival and are not dependent on the supply source.  The planned shipment, of course, is dependent on the supplying source and the transit lead time.

This make arrival based planning a powerful approach since it enables you to easily plan a change of source well into the future and have all the cascaded dependent demand reflect a valid simulation of reality.

Sides of a Coin

Most controversies would soon be ended, if those engaged in them would first accurately define their terms, and then adhere to their definitions. – Tryon Edwards

simple: easy to understand, deal with, use, etc.

simplistic: characterized by extreme simplism; oversimplified

complex: composed of many interconnected parts; compound; composite

complicated: difficult to analyze, understand, explain, etc.

Such small distinctions.

Such calamity when those distinctions are not properly acknowledged, particularly when applied to the retail supply chain.

Let’s start here:

  • Problems that are complex can usually broken down into smaller problems, each of which can be simple
  • Problems that are complicated are often intractable – they can’t easily be broken into chunks and require some sort of breakthrough to be solved (think peace in the Middle East)
  • Problems that are simple – well, they’re not really problems at all, are they?

Now here’s where – in my experience at least – retailers start running into trouble.

Problem #1: Seeing complexity as complication

If you’ve ever read articles about the challenges of planning the retail supply chain, you’ve probably seen a diagram or two that looks something like this (if not worse):

The implication is clear: The retail supply chain is a vast, sophisticated web of relationships between and among various entities. Not only that, but the problem becomes more mind boggling the closer you get to the customer, as depicted below:

I mean, look at all those arrows!

To be sure, the retail supply chain planning problem is large in terms of the number of items, locations and source/destination relationships. The combinations can get into the tens – if not hundreds – of millions.

But is it truly an enormous and complicated problem or merely an enormous number of simple problems?

In contradiction to the popular proverb, sometimes it’s necessary to focus on the trees, not the forest.

How you consider the problem will in large part determine your level of success at solving it. Complication is often a self inflicted wound (more on that later).

Problem #2: Seeing simplistic as simple

Just as overcomplication leads to trouble, so does oversimplification.

Best summed up by Albert Einstein:

People love this quote because they feel it very neatly sums up Occam’s Razor. Then they further reduce it to a design philosophy like “the simpler, the better”.

But the real power in that quote doesn’t reside in the first part (“Everything should be made as simple as possible.”), rather in the second: But not simpler.

In a retail planning construct, I’ve most often seen this line crossed when the topic is forecasting for slow selling item/stores. Demand forecasting as a discipline originated in manufacturing where volumes are high and SKU counts are low. As a consequence, most mature forecasting methods are designed to predict time series with continuous demand.

When you look at retail consumer demand at item/store level, a significant portion of those demand streams (often more than 70% for hardlines and specialty retailers) sell fewer than one unit per week.

So we have intermittent demand streams and tools that only really work well with continuous demand streams. So what’s the solution?

One of the most common responses to that question is: “Screw it. It’s not even worth forecasting those items. Just set a minimum and maximum stock value for ordering and move on.”

That position is certainly not difficult to understand, but is this really keeping it simple or being overly simplistic?

Here are some follow-up questions:

  • What if a particular item is fast selling at some locations and slow selling at others? Would you forecast it at some locations but not at others? How would a demand planner manage that?
  • If not every item in every location is being forecasted, then how do plan future replenishment volumes? Not just at the stores, but at DCs as well?
  • If not every item is forecasted, then it’s not possible to do rollups for reporting and analysis, so how do you fill in the gaps?

Because a simplistic solution was proposed that only addresses part of a complex problem, we have created a problem that is complicated.

This is akin to looking at a single tree without even recognizing that there are other trees nearby, let alone seeing a forest.

Things are only as complicated as you choose to make them, but they also may not be as simple as they seem.

Trust the process

Nick Saban is a brilliant college football coach and widely heralded as a football genius. At time of writing, his coaching record stands at 261 wins, 65 losses and 1 tie. He’s won 17 Bowl games along with 7 national titles (the most ever) and counting.

If you’re a fan of the Alabama Crimson Tide, in a state where college football is king, Saban is arguably more popular than Jesus. Fanatics think he is Jesus.

When asked about his unrivaled success, Saban offers a counter-intuitive philosophy that’s guided his coaching career, anchored on two fundamental principles:

  1. Don’t focus on the outcome
  2. Trust the process

Incredibly, Saban doesn’t focus on the result – which, for college football – like most sports – is whether you win or lose. Sure, make no mistake about it, Saban wants to win, it’s just he believes that the path to long term success is by trusting the coaching process.

His belief is that by coaching his team, repeatedly and without fail, so that they can execute their designed plays on offense and coaching schemes on defense, he’ll maximize his odds of winning. Losses are important to this process as it provides the team the opportunity to review the film and see where the process failed – either in execution or, sometimes, in coaching and design. Which leads to more coaching, practice and trust in the process.

Trusting the process is a philosophy that has served Saban and the Crimson Tide incredibly well.

We can learn a lot from Nick’s nuggets of wisdom.

Given that we’re often referred to as the Salty Old Sea Dogs of Flowcasting, it’s fair to say that we’ve been around the block a few times and, over time, changed our thinking often. No more than so than in developing, managing and measuring the retail forecasting/demand planning process.

For most retailers, the number of item/store products that sell less than 26 units a year (about 1 every two weeks) can be pretty significant – often comprising 30-50% of a retailer’s assortment. You wouldn’t expect to be as accurate in determining a forecast for these types of products, since there is a fairly large element of probability involved – as an example, based on history, you can feel confident that 1 unit sells every month but you’re not sure when it will be.

While it’s tempting to aggregate the lower level item/store forecasts up to a higher level and assess forecast performance, that’s of little use to anyone – after all, customers buy products in stores, or online, to be acquired or delivered at their preferred location. They don’t buy them at some aggregate level. Not to mention that item/store replenishment plans are driven from these forecasts and the dependent demand is cascaded throughout the supply network.

Like Saban, we work with our clients to help them understand and hopefully instill the idea of assessing the forecasting process by determining something called forecast reasonableness.

So then, what’s a reasonable forecast?

The following diagram outlines, conceptually, what we’re talking about:

The idea is to assess the reasonableness of the forecasts based on a sliding scale determined by selling rate. As an example, you wouldn’t expect to have as accurate a forecast for a product that sold 12 units a year as you would for something that sold 1200 units a year. Of course, you need to determine what’s a reasonable tolerance and sliding scale but from experience that’s not too difficult.

If the item/store forecast is within tolerance then the process/solution is producing a reasonable forecast. The beautiful thing is that the planner spends no time chasing these forecasts since, in all likelihood very little can be done to improve the process/outcome for these.

In practice, forecast reasonableness is an exception condition for the demand planners to action. For the item/store forecasts that are outside of tolerance, the planner can investigate these, see if the same item is outside of tolerance for a number of stores and determine if anything is systemically happening or could be improved in the process to bring them within tolerance.

To determine how well the forecasting process is working is simple. What percentage of the item/store forecasts is within tolerance?

We believe that, in retail, forecast reasonableness should replace traditional measures of forecast accuracy (like MAPE, WMAPE, etc., that were developed for more continuous demand streams in manufacturing and distribution).

Now before you think we’re completely mental, here’s something to ponder on. One of our retail clients, who plan using the Flowcasting process, does not measure baseline forecast accuracy.

Instead, they use a forecast reasonableness exception to evaluate the process, honing in on any forecasts that are not within tolerance to see if there is anything that can explain this and, potentially, how they might “improve the process”.
During the time they’ve not measured forecast accuracy they improved daily in-stock from an average of 91.7% to an average of 97.7%, while also improving inventory performance.

For a customer, in-stock is everything. They couldn’t care less about forecast accuracy.

Maybe you shouldn’t either.