“In years past companies have focused on demand side forecasting accuracies. SC managers are realizing the big gain is on supply side management.”

                                                    – Chris Barnes

An article I co-authored with George Stalk, Jr., “A Better Way to Match Supply and Demand in the Retail Supply Chain” was recently published by Harvard Business Review.  A colleague, who happens to go by the handle of “Supply Chain Doctor” made a profound comment on the underlying premise of the article.  He said… 

“The future of SCM is here. In years past companies have focused on demand side forecasting accuracies. SC managers are realizing the big gain is on supply side management. Whatever you can do to help your suppliers will pay dividends to your company. Not as glamourous as omni-channel distribution, but without strong supplier relations, omni-channel won’t really matter much.”

Loyal readers will understand that we’re talking about using the Flowcasting process to only forecast where it counts (i.e., the final point of sale) and to calculate all other inventory flows from consumption to supply.  This, of course, culminates in sharing planned shipments with suppliers – a concept referred to as supplier scheduling.

The concept of supplier scheduling has been standard practice in manufacturing for decades – that is, sharing a projection of future required product needs to help a manufacturer’s suppliers plan and deliver.  Flowcasting allows retailers and their manufacturing partners to leverage the same concept.

The planned shipments are the demand plan for the supplier for this retail customer – indicating how many units of each product will need to be shipped, when and where. This eliminates the need for the supplier to forecast demand for this customer.

From a supplier perspective, their major retail customers can provide them with calculated demand, rather than having to forecast it themselves.  Most CPG manufacturers would only require a handful of supplier schedules from their large retail customers to provide 70+% of their total demand.  They can forecast the balance. 

The projected requirements have all retail, supply chain and inventory flow constraints/rules incorporated, specific to each retail customer.  If a Retailer Customer was experiencing increased sales or had decided to change the shelf inventory requirements at a future date, the supplier schedule would reflect this in the planned shipment quantities. 

The Flowcasting model is based on a fundamental principle – a valid simulation of reality.  If the retailer and trading partners know the future will be different than the past, then these insights are factored into the forecast and resulting inventory flow plans, culminating in the supplier schedule. 

The impact of retailers embracing Flowcasting and supplier scheduling is significant.  It obsoletes a significant amount of non-value-added forecasting and, even more significant, effectively eliminates the bullwhip effect.

Perhaps we should listen to the Doctor’s orders.

Many thanks to Supply & Demand Chain Executive for publishing an article “Decimating Out of Stocks and the Bullwhip Effect”, written by Mike.

To read the article, click HERE.

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.

To read the article, click HERE.

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.

To read the article, click this link

1970s Montreal Genius

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.

“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.

Maybe, though, we’re all wrong.

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.

Jimmy really was a Jenius.

“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.

“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.