“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.