Tag Archives: Flowcasting

A Forecast By Any Other Name

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What’s in a name? That which we call a rose
By any other name would smell as sweet. – William Shakespeare (1564-1616), Romeo and Juliet, Act 2 Scene 2

Scenario 1: A store associate walks down the aisles. She sees 6 units of an item on the shelf and determines that more is needed on the next shipment, so she orders another case pack of 12 units.

Scenario 2: In the overnight batch run, a centralized store min/max system averages the last 6 weeks of sales for every item at every store. This average selling rate is used to set a replenishment policy – a replenishment request is triggered when the stock level reaches 2 weeks’ worth of on hand (based on the 6 week average) and the amount ordered is enough to get up to 4 weeks’ worth of on hand, rounded to the nearest pack size.

Scenario 3: In the overnight batch run, a centralized store reorder point system calculates a total sales forecast over the next 2 shipping cycles. It uses 2 years’ worth of sales history so that it can capture a trend and weekly selling pattern for each item/store being replenished and calculate a proper safety stock based on demand variability. On designated ordering days, the replenishment system evaluates the current stock position against the total of expected sales plus safety stock over the next two ordering cycles and triggers replenishment requests as necessary to ensure that safety stock will not be breached between successive replenishment days.

Scenario 4: In the overnight batch run, a centralized supply chain planning system calculates a sales forecast (with expected trend and weekly selling pattern) for the next 52 weeks. Using this forecast, merchandising minimums, store receiving calendars and the current stock position, it calculates when future arrivals of stock are needed at the store to ensure that the merchandising minimums won’t be breached over the next 52 weeks. Using the transit lead time, it determines when each of those planned arrivals will need to be shipped from the supplying distribution centre over the next 52 weeks. The rolled up store shipment projections become the outbound plans for each item/DC, which then performs the same logic to calculate when future inbound arrivals are needed and their corresponding ship dates. Finally the projected inbound shipments to the DC are communicated to suppliers so that they can properly plan their finished goods inventory, production and raw material procurement. For both stores and DCs, the plans are turned into firm replenishment requests at the ordering lead time.

With that out of the way, let’s do some audience participation. I have a question for you: Which of the above replenishment methods are forecast based? (You can pause here to scroll up to read each scenario again before deciding, or you can just look down to the very next line for the answer).

The answer is… they are ALL forecast based.

Don’t believe me?

In Scenario 1, how did the store associate know that a visual stock position of 6 units meant they were “getting low”? And why did she order a single case of 12 in response? Why didn’t she wait until there were 3 units? Or 1 unit? And why did she order 12? Why not 120?

For Scenario 2, you’re probably saying to yourself: “Averaging the past 6 weeks’ worth of sales is looking backward – that’s NOT forecasting!” Au contraire. By deciding to base your FUTURE replenishment on the basis of the last 6 weeks’ worth of sales, an assumption is being made that upcoming sales will be similar to past sales. That assumption IS the forecast. I’m not saying it’s a good assumption or that it will be a good forecast. I’m just saying that the method is forecast based.

Using the terms “trend” and “selling pattern” in Scenarios 3 and 4 probably spoiled the surprise for those ones.

So why did I go through such pains to make this point?

Quite simply, to counter the (foolish and naive) narrative that “forecasts are always wrong, so you shouldn’t bother forecasting at all”. 

The simple fact is that unless you are in a position where you don’t need to replenish stock until AFTER your customer has already committed to buying it, any stock replenishment method you use must by definition be forecast based. I have yet to run across a retailer in the last 28+ years that has that luxury.

A forecast that happens in someone’s head, isn’t recorded anywhere and only manifests itself physically as a replenishment request is still a forecast.

An assumption that next week will be like the average of the last few weeks is still a forecast.

As the march continues and retailers gradually transition from Scenarios 1, 2 or 3 to Scenario 4, the forecasting process will become more formalized and measurable. And it can be a lot of work to maintain them (along with the replenishment plans that are driven by them). 

But the overall effort pays off handsomely. Retailers in Scenarios 1, 2 and 3 have experienced in stock rates of 92-93% with wild swings in inventory levels and chronic stock imbalances. This has been documented time and again for 30 years.

Only by formalizing your forecasting your forecasting process, using those forecasts to drive long term plans and sharing those plans up and down the supply chain can you achieve 97-98% in stock while simultaneously reducing inventory investment, with reduced overall effort.

Collaborate, then calculate

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“Never forecast what you can calculate.” – Dr. Joseph Orlicky

Collaboration promises much to the retail supply chain, and rightly so. Retailers and their trading partners are beginning to understand they are not alone. The retail supply chain does not act as a series of islands – each independent entity working for its own purpose. Rather, smart companies understand that they are really working as part of one, completely integrated network that is designed (or should be) to deliver products to their end customers.

Almost 50 years ago, at the 1975 APICS conference in San Diego, Dr. Joseph Orlicky (the pioneer of MRP – Material Requirements Planning) made a profound statement regarding supply chain planning. Having just learned of Andre Martin’s idea to calculate factory demand from the distribution centre requirements, he told Andre that his idea was good since you should “never forecast what you can calculate”.

Leveraging this profound truth is the key to improved collaboration, addressing the shortcomings of CPFR and, importantly, making a significant dent in stock outs, overstocks, and the bullwhip effect.

The retail/CPG supply chain should be driven only by a forecast of consumer demand – time-phased by item/selling-location (e.g., store, webstore, etc.). The consumer demand forecast should then be used to calculate a series of integrated, time-phased product flow plans and planned shipments (for a 52+ week planning horizon) from the store to the supplier factory – what we call Flowcasting.

Sharing planned shipments allows the retailer to inform the supplier about future product flow requirements, by item and shipping location, with all known variables factored in – what we often refer to as the supplier schedule. This allows the supplier to eliminate all efforts previously expended to attempt to forecast that retailer orders. The planned shipments replace all this effort – improving the supplier order plan and allowing the collaborative process to work using the profound power of silence.

In the new collaborative model, since the planned shipments provide a long-term view of future required inventory flows, the expectation is that the retailer and supplier work to the principle of “silence is approval”. What that means is that the retailer expects the supplier to be prepared to deliver to the up-to-date, forward-looking schedule and only when they cannot supply to the schedule and/or they don’t understand the projected schedule, is collaboration required.

Collaboration based on a shared view of planned shipments (i.e., the supplier schedule) allows for the collaborative model to become more strategic and value added. In this new approach retailers and suppliers will collaborate on strategies to drive sales and potentially inventory plans – in essence, the inputs to drive joint business plans.

That’s a complete reversal of the traditional CPFR model where each company developed their own independent order forecasts and then spent considerable time and effort to reconcile these forecasts. In the new approach, the collaboration mostly focuses on a common language: sales to the end consumer. And, again, largely by exception. There is no need to collaborate on the plethora of retail forecasts and planned shipments since these have been automatically translated into the requirements, product flows and various languages of the business (e.g., dollars, cube, capacity, resource needs) for all trading partners.

The following diagram depicts the paradigm shift in collaborative planning between retailers and their merchandise suppliers – collaborating primarily on the inputs to the joint business plans, and only by exception if any issues or opportunities arise based on the resultant operational product flow plans:

Leading retailers and their suppliers will collaborate where they believe it is worthy of each partner’s time and largely on strategies (i.e., inputs to the joint plans) that drive growth and/or improved performance. That could be on promotional forecasts, new items, and ideas and concepts about product flows – to name a few. Both partners understand that the planned shipments resulting from these strategies are calculated – so collaboration on these shared projections is only needed if supply is at risk.

Dr. Orlicky’s famous and profound quote, “never forecast what you can calculate” is embedded in my mind and cemented in all the retail clients I’ve worked with. We can, and should, build on this profound truth and work to ingrain this thinking and practice between retailers and their trading partners…

Collaborate, then calculate.

Just In Time… For What, Exactly?

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

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

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

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

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

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

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

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

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

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

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

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

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

Changing the game

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In 1972, for my 10th birthday, my Mom would buy me a wooden chess set and a chess book to teach me the basics of the game.  Shortly after, I’d become hooked and the timing was perfect as it coincided with Bobby Fischer’s ascendency in September 1972 to chess immortality – becoming the 11th World Champion.

As a chess aficionado, I was recently intrigued by a new and different chess book, Game Changer, by International Grandmaster Matthew Sadler and International Master Natasha Regan.

The book chronicles the evolution and rise of computer chess super-grandmaster AlphaZero – a completely new chess algorithm developed by British artificial intelligence (AI) company DeepMind.

Until the emergence of AlphaZero, the king of chess algorithms was Stockfish.  Stockfish was architected by providing the engine the entire library of recorded grandmaster games, along with the entire library of chess openings, middle game tactics and endgames.  It would rely on this incredible database of chess knowledge and it’s monstrous computational abilities.

And, the approach worked.  Stockfish was the king of chess machines and its official chess rating of around 3200 is higher than any human in history.  In short, a match between current World Champion Magnus Carlsen and Stockfish would see the machine win every time.

Enter AlphaZero.  What’s intriguing and instructive about AlphaZero is that the developers took a completely different approach to enabling its chess knowledge.  The approach would use machine learning.

Rather than try to provide the sum total of chess knowledge to the engine, all that was provided were the rules of the game.

AlphaZero would be architected by learning from examples, rather than drawing on pre-specified human expert knowledge.  The basic approach is that the machine learning algorithm analyzes a position and determines move probabilities for each possible move to assess the strongest move.

And where did it get examples from which to learn?  By playing itself, repeatedly. Over the course of 9 hours, AlphaZero played 44 million games against itself – during which it continuously learned and adjusted the parameters of its machine learning neural network.

In 2017 AlphaZero would play a 100 game match against Stockfish and the match would result in a comprehensive victory for AlphaZero.  Imagine, a chess algorithm, architected based on a probabilistic machine learning approach would teach itself how to play and then smash the then algorithmic world champion!

What was even more impressive to the plethora of interested grandmasters was the manner in which AlphaZero played.  It played like a human, like the great attacking players of all time – a more precise version of Tal, Kasparov, and Spassky, complete with pawn and piece sacrifices to gain the initiative.

The AlphaZero story is very instructive for us supply chain planners and retail Flowcasters in particular.

As loyal disciples know, retail Flowcasting requires the calculation of millions of item/store forecasts – a staggering number.  Not surprisingly, people cannot manage that number of forecasts and even attempting to manage by exception is proving to have its limits.

What’s emerging, and is consistent with the AlphaZero story and learning, is that algorithms (either machine learning or a unified model approach) can shoulder the burden of grinding through and developing item/store specific baseline forecasts of sales, with little to no human touch required.

If you think about it, it’s not as far-fetched as you might think.  It will facilitate a game changing paradigm shift in demand planning.

First, it will relieve the burden of demand planners from learning and understanding different algorithms and approaches for developing a reasonable baseline forecast. Keep in mind that I said a reasonable forecast.  When we work with retailers helping them design and implement Flowcasting most folks are shocked that we don’t worship at the feet of forecast accuracy – at least not in the traditional sense.

In retail, with so many slow selling items, chasing traditional forecast accuracy is a bit of a fool’s game.  What’s more important is to ensure the forecast is sensible and assess it on some sort of a sliding scale.  To wit, if you usually sell between 20-24 units a year for an item at a store with a store-specific selling pattern, then a reasonable forecast and selling pattern would be in that range.

Slow selling items (indeed, perhaps all items) should be forecasted almost like a probability…for example, you’re fairly confident that 2 units will sell this month, you’re just not sure when.  That’s why, counter-intuitively, daily re-planning is more important than forecast accuracy to sustain exceptionally high levels of in-stock…whew, there, I said it!

What an approach like this means is that planners will no longer be dilly-dallying around tuning models and learning intricacies of various forecasting approaches.  Let the machine do it and review/work with the output.

Of course, sometimes, demand planners will need to add judgment to the forecast in certain situations – where the future will be different and this information and resulting impacts would be unknowable to the algorithm.  Situations where planners have unique market insights – be it national or local.

Second, and more importantly, it will allow demand planners to shift their role/work from analytic to strategic – spending considerably more time on working to pick the “winners” and developing strategies and tactics to drive sales, customer loyalty and engagement.

In reality, spending more time shaping the demand, rather than forecasting it.

And that, in my opinion, will be a game changing shift in thinking, working and performance.

Fossilized thinking

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Fossilized

In August 1949 a group of fifteen smokejumpers – elite wild land firefighters – descended from the Montana sky to contain an aggressive fire near the Missouri River.  After hiking for a few minutes the foreman, Wagner Dodge, saw that the fire was raging – flames stretching over 30 feet in the air and blazing forward fast enough to cover two football fields every minute.

The plan was to dig a trench around the fire to contain it and divert it towards an area with little to burn.

Soon it became clear that the fire was out of control and the plan was out the window.  The fire was unstoppable so, instead, they’d try to outrun it, to safer ground.

For the next ten minutes, burdened by their heavy gear and tiring legs, the team raced up an incline, reaching an area that was only a few hundred yards from safety.  But the fire was unflinching, gaining ground like a wolf chasing down a wounded animal.

Suddenly, Dodge stopped.  He threw off his gear and, incredibly, took out some matches, lit them, and tossed them onto the grass.  His crew screamed at him but to no avail – when Dodge didn’t listen, they had no choice and turned and ran as fast as they could, leaving their foreman to what they believed to be certain peril.

But Dodge had quickly devised a different survival strategy: an escape fire.  By torching an area in front of him, he choked off the fuel for the fire to feed on.  Then, he poured water on a rag, put it over his mouth and lay down, face first, on the freshly burnt grass while the fire raged and sped past and over him.  In total, he’d spend close to 15 minutes living off the oxygen close the ground he’d just torched.

Sadly, of the rest of his crew that tried to outrun the blaze, only two would survive.

Wagner Dodge was able to survive not because of his physical fitness, but his mental fitness – the ability to rethink and unlearn.  The prevailing paradigm was that, at some stage for an out-of-control blaze, your only option is to try to out run it.  But Dodge was able to quickly rethink things – believing that, perhaps, by choking off it’s fuel line and providing his own small wasteland area, the fire might avoid him.  The ability to rethink had saved his life.

As it turns out, the ability to rethink and unlearn is also crucial for retails survival and revival.

It’s no secret, many retailers are struggling.  The same is true of many retail supply chains.

Do you ever really wonder why?

Lots of people blame retail’s generally slow adoption of new technologies and business models as the main factor, but I think it’s a deeper, more fundamental and chronic problem.

Technology is not eating retail.  Fossilized thinking is.

What’s fossilized thinking?  It’s people – at all levels in an organization – who are unwilling or unable to challenge their long-held beliefs.  Not only challenge them, but be able to rethink, unlearn and change them often.

As a case in point, many people who work in the retail supply chain don’t include the consumer as part of the supply chain.  Yet, if you think about it, the retail supply chain begins and ends with the consumer.  There are even a number of folks who don’t consider the store part of the supply chain.  Once the product has shipped from the DC to the store, then, incredibly, job done according to them.

Don’t believe me?

I won’t embarrass them, but just recently I read a “thought leadership” article from one of the world’s pre-eminent consulting firms regarding the top trends in retail supply chain management.  At #3, and I kid you not, was the growing view that the store was a key part of the supply chain.

Flowcasting tribe members know better and think differently.  The consumer and store have, and always will be, part of the supply chain.  That’s why we understand that, in retail, there is no such thing as a push supply chain – since you can’t push the product to the consumer.

In my opinion (and I’m not alone), fossilized thinking, not technology adoption, is the real disruptor in retail.

If you want to improve, innovate or disrupt then you must…

Constantly rethink, unlearn and challenge your own thinking!

Limit your inputs

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Meditations

Marcus Aurelius is widely considered to be one of the wisest people of all time. His classic and colossal writings, ‘Meditations’, is a bible for crystal clear thinking, famously outlining the principles of stoicism.

In Meditations, he asks a profound question that all designers and implementers should ponder often…

”Is this necessary?”

Knowing what not to think about. What to ignore and not do. It’s an important question, especially when it comes to designing and implementing new ways of working.

As an example, consider the process of developing a forward looking forecast of consumer demand, by item, by store. Of course, loyal readers and disciples know that this is the forecast that provides a key input to allow a retail supply chain to be planned using Flowcasting.

You might get your knickers in a knot to learn that in one of our most recent and successful implementations of Flowcasting, the store level forecasting process uses only two key inputs:

  1. The actual sales history by item/store in units
  2. An indication if that sales history was during an abnormal period (e.g., a promotion, an unplanned event, a stock-out period, a different selling price, etc).

Now, I know what you’re thinking. What about all those ‘other’ things that influence consumer demand that many people espouse? You know, things like the weather, competitor activities and any other causal variables?

Counter-intuitively, all these additional ‘factors’ are not really required at the retail store level and for very good reasons.

First, did you know that for most retailers 50-60% of the item/store combinations sell 24 or less units per year. That’s less than one unit every two weeks. Furthermore, about 70-80% of the item/store combinations sell less than 52 units per year, or about 1 unit per week.

Consider the very slow sellers – selling 24 or less units a year. If the last 52 weeks sales was 24 units and so was the previous year’s, it would stand to reason that a reasonable forecast for the upcoming 52 weeks would be around 24 units.

Keep in mind, that as actual sales happen the forecasting process would always be re-forecasting, looking ahead and estimating the upcoming 52 weeks consumer demand based on most recent history.

Now, consider a 52 week forecast of 24 units. That breaks down to a weekly forecast of 0.46.

Factoring in additional variables is not likely to make actual sales of 30 units happen (assuming stock outs were not excessive) – which would be the equivalent of increasing previous year’s sales by 25%. A higher forecast does not mean sales will actually happen.

Even a 10% increase in the forecast would only increase the annual forecast by about 2 units, or about .04 units per week.

Is there really a difference between an average weekly forecast of 0.46 and 0.50 units? Isn’t that essentially the same number? In terms of a forecast, they are both reasonable (in reality, the forecast would also have a pattern to the expected sales and would be expressed as integers, but you get the point).

One of the keys of the retail Flowcasting process is using only a limited number of inputs to build the item/store forecast, while allowing people to easily understand and thus manage it – by a very limited number of exceptions that could not be automatically resolved using system rules.

Add some basic supply information (like inventory balances and ordering rules) to the forecast and voila – the entire supply chain can be calculated/planned from store to supplier – every day, for every planned inventory flow and projection for a rolling 52 weeks into the future.

What’s elegant and inherently beautiful about Flowcasting is that daily re-planning the entire supply chain provides the agility to adjust current and planned inventory flows and ensures everyone is working to a single set of numbers – based on the drumbeat of the consumer. It negates the need to find the ‘perfect forecast’ and, as such, allows us to limit our inputs to the bare essentials.

Marcus Aurelius was right.

Limit your inputs and always ask, “Is this necessary?”

It’s good advice in business, in life and especially store level forecasting.

Experts on the future

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In 1971, Judah Folkman, a doctor working in Boston, developed a new approach to treat cancer – essentially by stopping the blood vessels supplying the tumors. Blocking the flow, he concluded, would halt the growth of the tumors.

At the time, the only accepted and endorsed approach to treating cancer was chemotherapy. Dr Folkman’s idea was scorned and ridiculed by the medical establishment consisting of a group of PhD insiders – mostly from the field of biology.

According to Dr Folkman, when he attempted to share his idea and thinking to the scientific community, the entire room would get up and leave – as if, collectively, they all had to take a piss at the exact same time. Over time, the criticism got so bad that special committees were developed to review his ideas and not only judged his idea to be of little value, they also threatened to revoke his medical license if he did not cease – in one letter, writing to him to reject his ideas and calling him a ‘clown’.

Folkman, however, was undaunted and pressed on. Painstakingly, his ideas were slowly starting to be accepted by more “open” thinkers and eventually morphed into drugs available for cancer trials. To his credit, in the summer of 2003, at a major medical conference, the results from a large trial for patients with advanced colon cancer validated Dr. Folkman’s thinking.

The way to treat cancer had been transformed. At the event, the crowd rose in a standing ovation. The presenter, at the time, said, to the effect, “it’s a shame that Dr. Folkman couldn’t be here to experience this” – little did he know that, sitting in a back row, Dr. Folkman had just smiled.

Eventually he couldn’t hide his fame and was asked about his achievement – which had taken the better part of 32 years. Most folks wanted to know how he felt and why he continued on his journey in light of all the criticism and personal attacks.

His answers were and still are very insightful.

First, in terms of the ridicule he proclaimed, “You can always tell the leader of new thinking from all the arrows in their ass”.

And even more profound about why he never gave up: “There are no experts of the future.”

Presently we’re living through an unprecedented time and there are a lot of questions about the future – how will the world look after the virus is subdued and what will the new normal look like? Some of these questions are focused on retail and supply chain management.

How will consumers change their behaviors? How much sales will be transacted online? Will home delivery become even more significant? Will supply chain networks become more diverse and less susceptible to a single country’s supply disruption? What other customer delivery methods will emerge?

All good questions for which my answer is the same as yours, “I really don’t know”. In my opinion, a lot will change, I’m just not sure where, when, how much and how fast.

Remember, “There are no experts of the future”.

What I do know is that human behavior will not change. We are social animals and like and need to acquire stuff. We just might shift, perhaps dramatically over time, how we go about this.

For us supply chain planners – especially retailers – that means having the supply chain driven by and connected to consumer demand will be crucial. As consumer demand shifts and evolves having a complete model of the business and providing longer term visibility to all stakeholders will be a core capability – both in the short to medium term but also longer term to proactively plan for and respond to the next disruption.

Wait a minute…that sounds like Flowcasting, doesn’t it?

The key to being in-stock

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Key

Abraham Lincoln is widely considered the greatest President in history. He preserved the Union, abolished slavery and helped to strengthen and modernize government and the economy. He also led a fragile America through one of her darkest and most crucial periods – the American Civil War.

In the early days of the war, there were lots of competing ideas about how to secure victory and who should attempt it. Most of the generals at that time had concluded that the war could only be won through long, savage and bloody battles in the nation’s biggest cities – like Richmond, New Orleans and even Washington.

Lincoln – who taught himself strategy by reading obsessively – had a different plan. He laid out a large map and pointed to Vicksburg, Mississippi, a small city deep in the South. Not only did it control important navigation waterways, but it was also a junction of other rivers, as well as the rail lines that supplied Confederate armies and plantations across the South.

“Vicksburg is the key”, he proclaimed. “We can never win the war until that key is ours”.

As it turns out, Lincoln was right.

It would take years, blood, sweat and ferocious commitment to the cause, but his strategy he’d laid out was what won the war and ended slavery in America forever. Every other victory in the Civil War was possible because Lincoln had correctly understood the key to victory – taking the city that would split the South in half and gaining control of critical shipping lanes.

Lincoln understood the key. Understanding the key is paramount in life and in business.

It’s no secret that many retailers are struggling – especially in terms of the customer journey – most notably when it comes to retail out of stocks. Retail out of stocks have remained, on average, sadly, at 8% for decades.

So what’s the key to finally ending out-of-stocks?

The key is speed and completeness of planning.

First, we all know that the retail supply chain can and should only be driven by a forward looking forecast of consumer demand – how much you think you’ll sell, by product and consumption location.

Second, everyone also agrees (though few understand the key to solving this thorn in our ass) that store/location on-hands need to be accurate.

But the real key is that, once these are in place, the planning process must be at least done daily and must be complete – from consumption to supplier.

Daily re-forecasting and re-planning is necessary to re-orient and re-synch the entire supply chain based on what did or didn’t sell yesterday. Forecasts will always be wrong and speedy re-planning is the key to mitigating forecast error.

However, that is not enough to sustain exceptionally high levels of daily in-stock. In addition, the planning process must be complete – providing the latest projections from consumption to supply, giving all trading partners their respective projections in the language in which they operate (e.g., units, volume, cube, weight, dollars). The reason is simple – all partners need to see, as soon as possible, the result of the most up to date plans. All plans are re-calibrated to help you stay in stock. And the process repeats, day in, day out.

We have retail clients that are achieving, long term, daily in-stocks of 98%+, regardless of the item, time of year or planning scenario.

They understand the key to making it happen.

Now you do too.

Pissed Off People

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Jim is basically your average bloke. One Saturday afternoon, about 25 years ago, he’s doing something a lot of average blokes do; cleaning his home – a small farmhouse in the west of England.

After some dusting, it’s time to vacuum. Like everyone at the time, he’s shocked how quickly his top-of-the-line Hoover cleaner loses its suction power.

Jim is pissed. Royally pissed off. Madder than a wet hen.

So mad, in fact, that he took the cleaner out to his shed, took it apart and examined why it would lose suction power so quickly. After a few experiments he correctly deduced that the issue was that fine dust blocked the filter almost immediately and that’s why performance in conventional cleaners dips so fast.

Jim continued to be pissed until one day he visited a timber mill, looking for some wood. In those days, timber mills planed the logs on the spot for you. Jim watched as he saw his wood travel along until it reached a cyclone specifically designed to change the dynamics of airflow, separating the dust from the air via centrifugal force.

BOOM! James Dyson, still pissed at how shit traditional vacuum cleaners were, got the core idea of the Dyson cyclone cleaner. An idea that he would use to eventually deposit over £3 billion into his back pocket.

Unbelievably it took Dyson three years and 5,127 small, incremental prototypes to finally “perfect” his design and revolutionize cleaning forever. Can you imagine how pissed you’d need to be to work, diligently, over that many iterations to finally see your idea through?

Dyson’s story is incredible and enlightening – offering us a couple of key insights into the innovative process.

First, most folks think that innovation happens as a result of ideas just popping into people’s heads. That’s missing the key piece of the puzzle: the problem! Without a problem, a flaw, a frustration, innovation cannot happen. As Dyson himself states, “creativity should be thought of as a dialogue. You have to have a problem before you can have game-changing innovation”.

Second, for innovative solutions to emerge you need pissed off people. People like Dyson who are mad, frustrated and generally peeved with current solutions and approaches for the problem at hand. So they are always thinking, connecting and, at times, creating a breakthrough solution – sometimes years after initially surfacing the problem. So, while it’s easy to say that the “idea” just happened, more often than not you’ve been mulling it over, subconsciously, because you’re pissed about something.

Here’s a true story about Flowcasting and how it eventually saw the light of day as a result of some pissed off people.

About 25 years ago, I was the leader of a team whose mandate was to improve supply chain planning for a large, very successful Canadian retailer. I won’t bore you with the details but eventually we designed, on paper, what we now call Flowcasting.

Problem was that it was very poorly received by the company’s Senior Leadership team, especially the Supply Chain executives. On numerous occasions I was informed that this idea would never work and that we needed to change the design. I was also threatened to be fired more than once if we didn’t change.

The problem was, our team loved the design and could see it potentially working. As I was getting more pressure and “never” from the leadership team, I was getting more and more pissed. Royally pissed off as a matter of fact.

As luck would have it, as a pissed off person, I didn’t back down (there’s a lesson here too – “never” is not a valid reason why something might not work, regardless who says it). One person on the team suggested I contact Andre Martin and he and his colleague, Darryl Landvater, helped us convince the non-believers that it would be the future and that we should pilot a portion of the design. The rest is, of course, history.

The Flowcasting saga didn’t stop there. As we were embarking on our early pilot of the DC-supplier integration, Andre and Darryl tried, unsuccessfully, to convince a few major technology planning vendors that an integrated solution, from store/consumption to supply was needed and that they needed to build it, from scratch.

All the major technology players turned them down, citing lots of “nevers” themselves as to why this solution was either not needed, or would not scale and/or work.

To be honest, it pissed them off, as they’ve admitted to me many times over the years.

So much so, that, despite all the warnings from the experts they “put their money where their mouth is” and built a Flowcasting solution that connects the store to supplier in an elegant, intuitive and seamless fashion – properly planning for crucial retail planning scenarios like slow sellers, promotions, and seasonal items just to name a few.

In 2015, using the concept of Flowcasting and the technology that they developed, a retailer seamlessly connected their supply chain from consumption to supply – improving in-stocks, sales and profits and instilling a process that facilitates any-channel planning however they wish to do it.

Sure, having a reasonably well thought out design was important. As was having a solution suited for the job.

But what really enabled the breakthrough were some pissed-off people!

Covered in Warts

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It’s the early 1990’s and Joanne is down on her luck. A recently divorced, single mother who’s jobless, she decides to move back from England to Scotland to at least be closer to her sister and family.

During her working days in Manchester she had started scribbling some ideas and notes about a nonsensical book idea and, by the time she’d moved home, had three chapters written of a book. Once back near Edinburgh, she continued to write and improve her manuscript until she had a first draft completed in 1995 – fully five years from her first penned thoughts.

During the next two years she pitched the very rough manuscript to a dozen major publishers. They all rejected it and believed the story would not resonate with people and, as a result, sales would be dismal.

Undismayed she eventually convinced Bloomsbury to take a very small chance on the book – advancing her a paltry $1500 pounds and agreeing to print 1,000 copies, 500 of which would be sent to various libraries.

In 1997 and 1998 the book, Harry Potter by J. K. Rowling, would win both the Nestle Book award and the British Book Awards Children’s book of the year. That book would launch Rowling’s worldwide success and, to date, her books have sold over 400 million copies.

The eventual success of the Harry Potter series of books is very instructive for breakthroughs and innovation.

The most important breakthroughs—the ones that change the course of science, business, or history — are fragile. They rarely arrive dazzling everyone with their brilliance.

Instead, they often arrive covered in warts — the failures and seemingly obvious reasons they could never work that make them easy to dismiss. They travel through tunnels of skepticism and uncertainty, their champions often dismissed as crazy.

Luckily most of the champions of breakthrough items are what many would describe as loons – people that refuse to give up on their ideas and will work, over time, to smooth and eliminate the warts.

When it comes to supply chain planning innovation, you’d have to put Andre Martin into the loon category as well.

In the mid 1970’s Andre invented Distribution Resource Planning (DRP) and, along with his colleague Darryl Landvater, designed and implemented the first DRP system in 1978 – connecting distribution to manufacturing and changing planning paradigms forever.

Most folks don’t know but around that time Andre saw that the thinking of DRP could be extended to the retail supply chain – connecting the store to the factory using the principles of DRP and time-phased planning.

The idea, which has since morphed and labelled as Flowcasting, was covered in warts. During the course of the last 40 years Andre and Darryl have refined the thinking, smoothed the warts, eliminated dissention, educated an industry and, unbelievably, built a solution that enables Flowcasting.

I’ve been a convert and a colleague in the wart-reduction efforts over the last 25 years – experiencing first-hand the some irrational responses and views from, first, a large Canadian retailer, and more recently the market in general.

But, like JK, the warts are largely being exposed as pimples and people and retailers are seeing the light – the retail supply chain can only deliver if it’s connected from consumer to supplier – driven only by a forecast of consumer demand. Planned and managed using the principles of Flowcasting.

The lesson here is to realize that if you think you’ve got a breakthrough idea, there’s a good chance it’ll be covered in warts and will need time, effort, patience and determination to smooth and eliminate them.

It can, however, be done.

And you can do it.

Godspeed.