Our article, “A Better Way to Match Supply and Demand in the Retail Supply Chain” co-authored by Mike Doherty and George Stalk, Jr., published by the Harvard Business Review. The basic thesis of the article is that Flow-casting can address the most insidious problems in the retail supply chain – out of stocks, overstocks, and the bullwhip effect.
I’d like to thank Retail Insider magazine for publishing my article about “Managing a Retail Business to a Single Set of Numbers” – outlining the pioneering work of Andre Martin, Darryl Landvater, and Oliver Wight (Oliver Wight Americas, Inc.) from 40 years ago in manufacturing and how it can and does apply to retail.
To all my colleagues and clients around the world, you should read Retail Insider and subscribe to their Retail-Insider eNewsletter. They are both enlightening and bring valuable insights to the retail community.
If you happen to be a long-time fan of the Montreal Canadiens hockey team, then undoubtedly the late 1970s was a dream for you. The Habs were on a tear, winning 4 consecutive Stanley Cups and playing some of the fastest and best hockey ever seen.
In the late 1970s there was another Montrealer who was on a tear as well, in this case with respect to inventory flow planning innovation.
In 1975, as Director of Manufacturing Operations and Distribution, Andre Martin lead the creation, development, and successful implementation of the first integrated time-phased planning system in industry. Andre leveraged the Bill of Material (BOM) concept to integrate manufacturing operations from distribution centre to factory floor. Instead of a BOM, he flipped the idea and developed the concept of a Bill of Distribution (BOD). Once we forecast the demand at the DC’s, he reasoned, we could calculate the dependent demand onto the factories.
The Distribution Planning solution was aptly named Distribution Resource Planning (DRP) and adhered to the mantra laid out by Dr. Joseph Orlicky (of Material Requirements Planning fame) to “never forecast what you can calculate”. This in-house development and implementation enabled Abbott to seamlessly manage the flow of products across a three-echelon supply chain – a worldwide supplier network supplying to three factories (Montreal PQ, Brockville ON and Toronto ON), and ten distribution centers across Canada.
Prior to managing manufacturing and distribution operations Andre worked in accounting and finance. Having this accounting background, and coupled with his experience in manufacturing and distribution, Andre realized that they needed to tie their new time-phased inventory flow planning system with Abbott’s financial system.
In 1978 he saw the opportunity of enabling Abbott’s top management team to manage their business to “A Single Set of Numbers” – converting the forecasts and resulting plans into financial, resource and capacity projections.
He also realized that the new DRP solution, along with the DRP/MRP integration could be used as a financial planning and budgeting tool. The projections would form the foundation for the annual plan. As a result, Abbott’s top management was able to use their operating system to put together their 1978 annual budget using the very same system they used to manage their day-to-day business.
Oliver Wight, Abbott’s consultant at the time, created the term Manufacturing Resource Planning, or MRPII, to describe this broader application of the solution and the rest is history.
Loyal readers and disciples (yes, we have a few of those but would love several thousand more!) will realize that Andre’s pioneering work is also relevant and applicable in retail.
For example, consider Canadian national hard lines retailer Princess Auto Ltd (PAL). PAL plans inventory using the Flowcasting process—developing consumer-driven, integrated inventory flow plans that are valid across the entire value chain, including plans that span multiple organizations. Every department—including suppliers—use the projections for planning and to identify opportunities to improve service, cost, and productivity.
The item/store forecasts in units are converted to financial sales projections, and then aggregated to category, department, and sub-department level to provide the starting point for the baseline budget for the upcoming year. The impacts of additional strategies and tactics are then added to the calculated baseline to arrive at the budget, or business plan.
Given the new planning process is always recalibrating based the on the latest information, it has provided the Leadership Team with a continuous, forward-looking critique of how well the business plan is being realized – essentially a Retail Sales and Operations planning process. Instead of looking in the rear-view mirror to evaluate the plan, the Leadership Team has the capability to assess the forward-looking plan and determine where the plan may be at risk – giving them time to make any adjustments necessary to stay on track.
More importantly, they are managing their business to a single set of numbers – having essentially a model of how they wish to do business, spanning their entire eco-system.
It’s a concept that originated in Montreal over 40 years ago – thanks to the pioneering work of, among others, Andre Martin, Oliver Wight, Darryl Landvater and Abbott Labs – and is being realized today by smart, forward-thinking retailers like Princess Auto Ltd.
More Genius from the 1970s
Did you know that during this time, Andre also invented a concept called Game Planning?
He converted the time-phased production plans (developed by calculating production requirements from the DRP-driven plans) to dollars and called it “Game Planning” – since it produced a dollarized view of planned sales, production, shipments, and inventory levels (i.e., essentially the company game plan) for a 2-year planning horizon. The combined views of financial and resource projections allowed Top Management to gain better control of the business.
In the early 1980’s, an Oliver Wight Associate named Dick Ling renamed Game Planning to what it’s referred to today – Sales & Operations Planning (S&OP).
The late 1970s was a special time for the Montreal Canadiens.
The late 1970s was also a special time for Andre Martin.
Nothing is less sincere than our mode of asking and giving advice. – Francois de la Rochefoucauld (1613 – 1680)
Actually, that quote above the title block is only partial. Here’s the entire quote:
Nothing is less sincere than our mode of asking and giving advice. He who asks seems to have a deference for the opinion of his friend, while he only aims to get approval of his own and make his friend responsible for his action. And he who gives advice repays the confidence supposed to be placed in him by a seemingly disinterested zeal, while he seldom means anything by his advice but his own interest or reputation. – Francois de la Rochefoucauld (1613 – 1680)
It’s with that context in mind that I’d like to discuss so-called “customer satisfaction” surveys.
If you use Microsoft Teams, you’ve certainly seen this pop up after ending a call:
If you give them 5 stars, you see this:
Aw, that’s nice. However, if you give them 4 stars (or anything below 5 stars), you get this:
If you click on one of the “Audio”, “Video” or “Presenting” links (I selected “Video”), you get this:
And after checking the box that best describes your problem, you get this:
TRANSLATION: “Thanks for the feedback! It’s been saved somewhere for someone to look at someday – maybe.”
The most cynical (or paranoid) interpretation of this is that they are trying to train their customers to either give them the highest possible rating or skip giving feedback altogether. “If you give us 5 stars, you can move on with your day. Anything less than 5 stars, and we’re giving you work to do.”
A kinder interpretation is that they didn’t really think through their data collection method, as it’s clearly flawed and unlikely to give them anything useful.
It should be noted that I’m not picking on Microsoft here (and if I were, they would hardly care). Their feedback collection has actually improved recently by at least trying to make it easier to get something useful from their users.
More often than not, the only option after giving fewer than 5 stars is something like: “Oh, we’re sorry to hear that. Please type a short essay into the box below explaining your problem and NOBODY will get back to you.”
But it’s not just online. At my favourite grocery store (which I won’t name), every cashier has started asking me “Did you find everything you were looking for today?”
If I reply “Yes”, the cashier will respond with something like “That’s good to hear!”
If I reply “No, I needed black beans for a recipe, but you’re all out”, the response is something like “Oh, I’m sorry to hear that.”
That’s it. End of conversation.
If I were more of a jerk, I would ask them “Aren’t you going to write that down? Don’t you want to know the brand and size I was looking for? Aren’t you going to call a supervisor to talk to me about it?”
Of course, I’m not going to do that – the cashiers are just doing what they’ve been asked to do. I imagine this extra little task at the end of each transaction opens them up to abuse from people who ARE jerks and don’t understand that the cashier has zero control over stock availability in the store.
Now when I get asked this question, I just say “Yes”, regardless of whether it’s true or not.
Okay, so now that I’ve done my complaining, I’ll propose a couple of nominal solutions:
If you don’t care about my feedback, don’t ask. I’m actually being sincere here. I find not being asked preferable to feigning interest in my experience for the sake of having an interaction, while making it quite obvious at the end of the interaction that you really don’t give a shit.
If you actually do value the feedback, then do SOMETHING to show it other than saying “Thanks for that, now leave me alone.”
Just spitballing here, but in the MS Teams example, what if they linked you to a simple support page that describes the most common causes of the problem you indicated with some quick fixes to try?
Or at a minimum, they could tell you exactly what happens to your feedback after you hit Submit and send a follow-up message whenever they’ve actually done something on their end to address the problem you raised.
As for the retail store example, the most obvious sincere remedies for a customer expressing dissatisfaction at the checkout (offering to switch to a higher priced brand, providing a discount on the order or a gift card for a future trip, etc.) are all admittedly very costly and/or rife with the potential for abuse. But could you at least have a tally sheet next to the cash register where a cashier can record which department is logging the most customer complaints to see if there’s an operational issue?
Or better yet, provide me with an app on my phone that allows me to scan and report the empty shelf for the item I wanted to purchase. Then you could follow up with me electronically later to let me know when it’s available, maybe send me a discount coupon for it, etc.
Look, every customer feedback mechanism has its flaws, but if you’re just fishing for compliments (or punishing customers for lodging complaints), then you’re not really collecting any useful information anyhow, no matter how “cheap and easy” it was to do.
And when a customer gives you negative feedback without any follow-up, then that’s just one additional thing you’ve done to annoy them today.
“Work alone. You’re going to be best able to design revolutionary products and features if you’re working on your own. Not on a committee. Not on a team.”
– Steve Wozniak
In 1963 Marvin Dunnette, a psychology professor at the University of Minnesota performed an experiment that challenged conventional wisdom, yet few people know about it and even fewer have learned from it.
Dunnette gathered 48 research scientists and 48 advertising executives, all of them from 3M, and asked them to participate in both solitary and group brainstorming exercises.
He divided the group into twelve teams of four. Each foursome was given a problem to brainstorm, such as the benefits or difficulties of being born with an extra thumb. Each man was also given a similar problem to brainstorm on his own. Then Dunnette and his team counted all the ideas, comparing those produced by the groups with those generated by people working on their own.
The results were startling and counter-intuitive. The men in 23 of the 24 groups produced more ideas and of better quality when they worked on their own rather than in a group.
Since then some forty years of research and studies have shown that, almost always, performance gets worse as the group size increases. The “evidence from science suggests that business people must be insane to use brainstorming groups”, wrote the organizational psychologist Adrian Furnham.
When it comes to forecasting, collaboration is the accepted conventional wisdom. Consider retail supply chain forecasting. Most of us believe that collaborating with multiple people, potentially including the supplier, produces a better forecast. Yet, Dunnette’s research would suggest otherwise.
Perhaps better results could be achieved if forecasting was solely left to the retailer? And, further, to one person who is focused on a specific category of products. Then, using the Flowcasting process, this forecast of consumer demand would be translated into all other demand, supply, capacity, and financial plans for all partners in the supply chain.
But wait, you say, having the input of lots of people can materially improve the quality of the forecast. Sure, we all say that, but how specifically? It’s just accepted practice that if multiple people work on the forecast, then it will be better. Just like group brainstorming produces better results.
Do we think the forecast can be improved for promotional forecasts by having more people collaborate? Again, how exactly?
If you think about forecasting consumer demand isn’t the retailer closer to the consumer? Haven’t they got all kinds of information regarding past promotions for the item in question and similar items (likely from another supplier)?
Don’t they have a complete view of other marketing and promotional activities that might impact specific products being forecast at the same time? And isn’t this information available to the demand planner accountable for the forecast?
If two people were tasked with developing a forecast of consumer demand for a promotion and had the same inputs and history as a starting point, how different would their forecasts really be?
It’s a question that’s seldom asked.
Maybe, retail supply chain forecasting would be better served with one forecast, created by the retailer, owned, and managed by one person – and with the advances in Artificial Intelligence and Machine Learning, managed by reviewing only a miniscule number of exceptions that the machine couldn’t understand yet.
It’s counter to the collaboration Kool-Aid we’ve all been drinking for years. And to what most supply chain practitioners say.
While the pandemic has recently pushed the trend into overdrive, click & collect has been steadily growing for years. And by all accounts, it will continue to grow in the years to come.
The two main reasons most often cited for why click & collect is so popular with consumers (versus home delivery) are:
Avoidance of delivery charges
Faster fulfillment (i.e. they can most often get the items they’re looking for at a nearby location on the same day, rather than waiting for it to ship from a remote fulfillment centre)
What seems to have escaped notice is that there’s another fulfillment method that delivers both of those benefits to customers: Driving to the store, getting the product themselves and bringing it home.
In fact, with regard to the second benefit (faster fulfillment), the “go get it yourself” method is superior. Depending on how far away the store is, a customer can have an item in his/her possession within minutes of deciding they want it, without having to wait for a pickup email.
This begs the question (that nobody seems to be asking, at least as far as I can tell): For customers who are looking to avoid delivery charges and fulfillment delays, why would they choose click & collect versus just picking it up themselves, given that both methods require a trip to the store anyhow?
In the absence of surveys or studies on this topic, I’ll postulate an explanation based on my personal experience. I do frequently use click & collect, but not because I find it convenient. I use it as a tool to avoid inconvenience.
Here is an early version of my personal “click & collect customer journey”:
I determine that I have a need for Product A.
I know that Retailer X sells Product A and that Retailer X has a location (Store 1) near me.
I check Retailer X’s website and it shows that they have 6 on hand at Store 1.
I drive to Store 1 to pick up one unit of Product A.
When I get to Store 1, the shelf is empty. I ask a team member to help me, but after 10 minutes of searching, they can’t find it either.
I angrily drive home and look up Product A at Store 2. It’s not as close, but still within a reasonable driving distance. The website shows that Store 2 has 4 units on hand.
Before driving to Store 2, I place a click & collect order for Product A and wait for the pickup email. Even though I have time to go get it now, I’m not in a particularly trusting mood – I’m not willing to spend more time and gas driving there only to find that Store 2 is out of stock too.
The pickup email doesn’t arrive that day, so I go to bed.
The next afternoon, I receive a “your order has been cancelled” email from Store 2. I check the on hand balance on the website and it now shows that Store 2 is out of stock on Product A. Clearly they went to pick it, couldn’t find any and zeroed out their on hand balance.
I give up and order Product A from Amazon and just wait for it to be delivered to my home (so much for the click & collect benefits).
On the basis of that experience, I’ve streamlined the process to jump straight from step 1 to step 7 – let the retailer spend their time and energy trying to find it before I waste any of mine.
To be sure, there are some customers out there who do find click & collect “convenient” in its own right – being able to (hopefully) get what they want on the same day without having to push a cart through the aisles, even though they still need to make a trip to the store.
But in many cases, click & collect may not be the “win-win” that everyone is claiming it to be. Customers aren’t necessarily rewarding retailers for providing added convenience – they may be punishing them after being burned for poor in stock performance now that click & collect has given them the opportunity to do so. And retailers now need to pay staff to perform tasks that customers used to do for free, in addition to losing out on impulse purchases and cross-selling opportunities in the store.
Perhaps retailers should be working harder on the basics (keeping stock accurate, in stock and on the shelf) to make it truly convenient for customers to get what they want where they want it and when they want it.
It’s funny how you sometimes recall something from years ago, often triggered by a recent event, and it helps to cement or solidify your thinking.
Flashback to 1992 and, after working for a prestigious Canadian Management Consultancy since my 1986 graduation, I decide it’s time to leave consulting and get an industry job. I’d land at National Grocers (NG), at the time the distribution and logistics division of Loblaw Companies Limited. My job, along with the newly minted Director (who was a colleague from consulting), would be to establish the logistics function in the company – taking an end-to-end view of the entire supply chain, both from a technology and physical flow perspective.
NG, at the time, had retained Jim Woods, the former VP of distribution for Kroger – the massive US based grocer – in an advisory role. He was full of stories, ideas, insights and on some days, other stuff as well. On most Friday’s we’d head to a restaurant called The Greek to listen to Jim’s Jenius, so to speak. One thing he said to me that I’ll never forget went something like this…
“Mike, I’m not sure what the future of supply chain will be but the best advice I can give you is never slow the product down”.
I was intrigued and have subconsciously been pondering that ever since.
I recently read an awesome book, Arriving Today, chronicling the global journey of a single USB charger, from factory to front door. A couple of chapters highlighted and not only solidified the advice Jim gave me thirty years ago, but likely outlines the fundamental paradigm shift of retail supply chain management.
As the USB chargers make their way to an ultra-modern Amazon fulfillment centre, what blew me away is what happens next, architected on Amazonian principles. The inbound shipment of USB chargers is de-palletized, and each individual USB charger is stored, in single units, in a random bin that the system had moved to the receiver.
So, a receiver would store a shipment of 48 chargers, randomly in 48 different bins amongst several shelving units. Storing items randomly mimics the basic architecture of computers and the process is called “random stow” – the idea that the best way to get products in and out of shelves in a warehouse is to put them anywhere they’ll fit, rather than trying to design some sort of system to organize them.
In addition to the significant improvement in storage capacity, the individuating of products facilitates something even more profound – optimizing for and enabling the each-supply-chain. Amazon has architected its supply chain for the consumer, rather than distribution – recognizing that most customer orders are in units of one (i.e., each-es), rather than cases or pallets. When a customer orders one of these USB chargers, then a bin is selected that contains only one charger and is moved to an order filler to select this single unit and get the order on its way.
Most retail supply chains are distribution-centric, rather than consumer-centric.
But could Amazon be onto something here? What if we applied the same thinking to a modern omni-channel retailer, complete with a network of distribution centres and stores?
Surely, I’m not saying to ship in each-es, both to the consumer and to replenish the stores. Um, er,…, that’s exactly what I’m saying.
Most retail supply chains don’t heed Jimmy’s advice. They slow the product down by shipping in cases and pallets. The conventional wisdom says that you need density to fill up trucks to go to the stores and most supply chain folks have ingrained the paradigm that larger shipments, by product, saves considerable handling costs.
All true, to a certain extent, but have you considered the other costs and benefits of architecting flows to the consumer?
First, outbound trucks from DC’s to stores could still be filled – it’s just the composition would be smaller, individual product shipments. The ability to stay in stock would be improved, since the inventory at each DC would only be shipped in units of one (or smaller shipments), rather than cases. In addition, in virtually all situations, product could flow directly to the shelf.
In two recent retail clients, both demonstrated that inventory accuracy improved significantly for products where the required inventory fits on the shelf selling location – rather than having top stock, overstock, or backroom stock. For these types of products, the inventory accuracy was 85%+, a significant improvement from the retail average of 50-60%.
This would be true for all stores and would also be an important benefit for consumers – since they are asking retailers to display their inventory availability, as evidenced by this recent Forrester research of US consumer expectations:
• 65% say it’s important for retailers/brands to show in-store product availability on the website • 68% think it’s important to know when items will arrive, before placing orders online • 30% checked for a product online before purchasing it in a store • 33% are less likely to go into a store if inventory is not available online
In addition, replenishing in each-es could have a very significant impact on store inventories and space. I recently took a random store from a recent client and compared the inventory and space requirements from their current distribution-centric replenishment philosophy (i.e., replenishing in cases) to a consumer-centric philosophy (i.e., replenishing in each-es) and the impact was significant. Both overall inventory and space requirements were 40-50% less.
Now, of course, I realize that costs in the distribution centre will increase and the flows and operations inside these facilities would need a complete re-think and potentially a new operating model. However, if you step back and think about the retail supply chain, and include the consumer in it, it changes your perspective.
Online demand is usually in each-es. For most retailers, a significant percentage of item/store sales are less than one per week. Thus, I’d argue that we’re largely operating in an each-supply-chain today and that will likely proliferate in the years ahead. The issue is that we’re still burdened with distribution-centric thinking, slowing the product down and altering product flow as a result.
“Never slow the product down”.
It was great advice in 1992 and even better advice today.
Here’s my high level analysis of the technology landscape for retail planning systems:
I’ve seen systems that intersect with any two of those circles, but I’ve never seen one in the “sweet spot”:
Built for retail
Holistic supply chain planning capabilities
Commercially available with a solid track record
Built For Retail and Commercially Available, Limited Supply Chain Planning Capabilities
Systems falling into this category generally have the “look and feel” that retailers are looking for and speak the language that most retailers find natural: orders. Suggesting orders. Optimizing orders. Managing the release of orders.
Over time, these systems have evolved to include long term demand forecasting, time-phasing out their ordering logic into the future and even connecting time-phased store order plans to distribution centres in an attempt to encroach into the “Supply Chain Planning Capabilities” circle. But the logical DNA of these systems is to work out the administrative part of the supply chain (the orders) first and understand the shipments and arrivals after the fact.
While these systems are demonstrably and significantly superior to traditional reorder point and min/max approaches when it comes to replenishment, they struggle to provide a valid simulation of reality that can be rolled up to support flow planning, capacity planning and business/financial planning, particularly in scenarios where the “steady state” is being disrupted:
Changes to network flowpaths, such as realigning DC outbound schedules or changing the inbound source of supply
Properly constraining ship dates for things like Chinese New Year and scheduled supplier shutdowns
Properly constraining arrival dates to account for receiving schedules at stores or DCs
These systems are generally streamlined and slick, but will struggle when the following question is posed:
How would you configure the system to accurately plan for a scenario where we are currently sourcing a bunch of items domestically, but will start sourcing those same items from overseas in 5 months?
Supply Chain Planning Capabilities and Commercially Available, Not Built for Retail
Systems falling into this category trace their lineage back to manufacturing and distribution where the discipline of supply chain planning began. Planning stock movement in a backward stepwise fashion from demand to supply (i.e. demand triggers arrivals which trigger shipments which trigger orders for every item at every location) is built right into their DNA.
Over time, these systems have evolved to be able to process the gargantuan data volumes common in retail, but only through brute force and by the grace of Moore’s Law. And bolt-ons have been developed to plan for things like retail promotions and intermittent demand streams in an attempt to encroach on the “Built for Retail” circle.
While these systems excel at being able to holistically plan stock movement from source of supply to source of consumption, it only comes with unnecessary complexity. It’s not easy to genetically modify a system that was built for manufacturing and distribution into a retail solution. These systems are designed to follow the core principles of planning, but will struggle when posed with the following question:
How would a planner update their forecasts and safety stocks for 20 items across 500 locations, roll up the results and then make a few tweaks – all before 10am (on the same day)?
Built for Retail with Supply Chain Planning Capabilities, Not Commercially Available
Systems falling into this category have successfully translated the time-tested planning capabilities originated in manufacturing and distribution to specifically tackle the retail planning problem in a way that’s simple, intuitive and fast.
The biggest problem these systems face is the huge barrier to entry into the market. In spite of their shortcomings, the types of systems discussed previously have developed a track record for delivering significant benefits to their retail customer base – suboptimal planning is better than no planning at all.
These systems have everything retailers need (from a stock flow planning standpoint) and nothing they don’t. But in my experience, retailers aren’t generally known for their willingness to gamble on something new and unproven at scale. They will struggle when posed with the following question:
Tell me about your last 5 full scale implementations at a retailer our size with similar planning challenges?
If you’re a software provider (or a user of said provider) who thinks you’ve hit the trifecta, then I guess I’m implying that you don’t exist. Even though I have never heard of you, I would be thrilled to get to know you.
“Education is the most powerful weapon you can use to change the world.”
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.
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.
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
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?