Tag Archives: Flowcasting

Marketplace Perceptions Rarely Reflect Reality (at least in this case)

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What’s wrong with this picture?

Back in 2014, Lora Cecere (a well-regarded supply chain consultant, researcher and blogger) wrote a post called Preparing for the Third Act. She said “JDA has used the maintenance stream from customers as an annuity income base with very little innovation into manufacturing applications. While there has been some funding of retail applications, customers are disappointed.”

Our experience is consistent with Lora’s assessment. We’ve been working in the trenches on this for the last 20 years and that opinion is also shared by many of our colleagues in the consulting ranks.

In fact, we have first-hand experience with customers who have been disappointed and with customers who are delighted. That puts us in a unique position.

What’s going on now makes no sense. You can buy the software that disappoints, but you can’t buy the software that does not disappoint. To make things even more absurd, the same company (JDA) has both software packages in its stable.

Retailers agree that planning all of their inventory and supply chain resources based on a forecast of sales at the retail shelf makes perfect sense. Additionally, manufacturers agree that getting time-phased replenishment schedules based on those plans from their retail customers provides significant additional value across the extended supply chain.

But because you can only buy the software that disappoints, most of the implementations will likewise be disappointing. Consequently, the perception of these systems in the marketplace is fairly negative.

It shouldn’t be. These systems can work very well.

First, a brief history of where this all started and how we got where we are today.

Initially, retailers had a choice between time-phased planning software designed for the manufacturing/distribution market or software designed for retail that couldn’t do time-phased planning.

Later, software was developed specifically for the mission: time-phased planning at store level. It could handle gigantic data volumes economically, is easy to use and easy to implement. It’s suitable for a small company (a handful of stores) and has been tested with volumes up to 450 million item/store combinations on inexpensive hardware.

Unsurprisingly, a square peg forced into a round hole (systems initially designed for use in manufacturing plants and distribution centres being applied to store level) yielded the disappointing results.

Also unsurprisingly, a system designed specifically to plan from store level back to manufacturers works just fine. In fact, our client (a mid-market Canadian hard goods retailer) is now planning every item at every store and DC, sharing schedules with suppliers, managing capacities and achieving extraordinary business results.

No doubt, the problem has been solved.

So what’s the path forward?

It’s in everybody’s best interest to work together.

From JDA’s perspective, this is a new wide-open market for them – and it’s enormous. But it won’t be developed if the marketplace perceives that implementing these systems delivers disappointing results.

In the event that JDA were to develop a new system with new technology and features appropriate to a retail business, they still need to build it, sell it to some early adopters, get it working well and rack up a few unequivocal success stories before they can begin to overcome the current level of customer disappointment.

How long will all of that take? An optimistic estimate would be 2 years. A realistic one is more like 3-5 years. Will there still be a market then?

From the retailer’s and manufacturer’s perspective, they can be saving tens to hundreds of millions of dollars per year (depending on size) and providing a superior consumer experience.

From the consultant’s point of view (the people who recommend and implement these systems for a living), having the ability to implement the software that isn’t being sold – but has been proven to work – will increase the number of implementations with outstanding results (rather than disappointing results). The net effect of this is that JDA will have more revenue and more success than if they continue to keep this software off the market. JDA has made this type of arrangement with other partners to their mutual benefit, without head-butting or causing confusion in the marketplace.

It could be that JDA is too close to the problem to see this as a solution.

Maybe Blackstone can look at situations like this more objectively and without bias, unencumbered from all that’s transpired to date.

Small data

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Lowes Foods, a family-owned grocery chain with stores located throughout North and South Carolina, is one of the region’s largest retailers, but in the late 2000’s they had a problem.

Declining revenues, triggered by the onslaught of ultra-competitors like Walmart and Amazon threatened the very existence of this 100-or-so retail chain, and unless something was done Management contemplated the closing of a number of stores – which, as everyone knew, would really flip the switch to the inevitable death-spiral of cost cutting and downsizing.

Fortunately, Management took action.  They turned to data analytics to help – even before analytics was in vogue. But instead of utilizing what now is known as Big Data, they retained an analytics expert in a different, and more important, field.  The retained the services of Martin Lindstrom.

Martin is one of the world’s leading branding experts and, arguably, the leading guru in a different form of analytics.

He’s a genius using Small Data to uncover stunning and brilliant insights that, in turn, form the basis of new strategies and tactics that help organizations, like Lowes Foods, thrive.

Instead of slicing and dicing volumes of data – which, as a retailer, Lowes had – his work focuses on very small learnings and observations about customers and indeed, Americans in general.

It’s his contention that Small Data, done well, provides the insights and clarity needed that are almost impossible to find with volumes of data.

Big Data is about information. Small Data is about people – finding the needle in a haystack.

For Lowes, he studied American culture – everything from values and beliefs but importantly very small clues that helped formulate his insight and strategy for Lowes.

As an example, he noticed that American hotels are hotels where the windows are locked.  Coupling that with the number of gated communities and a few other small clues, he concluded the following: despite what they tell you, Americans live in fear.

Studying people around the world, one person at a time, he concluded that the last time people were not afraid was when they were children.  Kids, regardless of culture, are by and large care-free.

So his strategy centered on making Lowes Foods more kid-like.  More fun. More entertaining. The place to go.

The entrance was revamped to include both ChickenWorks and SausageWorks – where busy shoppers could buy ready-made meals.  However, in keeping with the kids theme, the purveyors behind each offering were dressed up characters, complete with costumes that put on a show all day long.  They would argue, shout at each other and generally give each other the gears.  It was pure retail-tainment.

Now, Lowes Foods was always known for the quality of its fresh prepared chicken. In keeping with his insights, Lowes also implemented a new ritual.  When batches of new chickens were removed from the oven, a notice came over the loud speaker and all employees, including Management, would break into their “happy chicken dance”, accompanied by a specific ditty to celebrate hot, fresh, quality chicken.

Another important piece of small data Martin leveraged was the passing of business cards in many cultures. In many cultures, how you hand your business card to someone is an important sign of respect and is done by slightly bowing down and passing the card with two hands.

This small data insight led to a change in how ChickenWorks dealt with customers. Now, purveyors of the chicken would pass the chicken to customers using two hands, while slightly acknowledging the customer in the process. This signals respect to the customer and that what is being bought is of high value – both for the customer, and also for the employee.

All small insights. All based on Small Data – observations and learnings by watching and talking to one person at a time.

And it worked. Sales of ChickenWorks and SausageWorks skyrocketed. And Lowes Foods became known as the place to shop – a fun, unpredictable establishment where customers could buy good quality products, but enjoy themselves in the process.

For us supply chain planners, we’re bombarded every day with people touting the virtues and significance of Big Data. And, to be fair, Big Data is and will be important.

But so is Small Data. Small Data provides insights about people. Small Data opens clues to problem resolution that Big Data would suffer to uncover.

Small Data often provides the tiny clues and insights that drive real, significant change. Here’s a great example from supply chain planning.

For long time readers of our blog you know that the capability now exists to forecast and plan slow and very slow selling products at store level (or any final point of consumption). Hopefully you’re also aware that this allows us to Flowcast every product – that is create time-phased sales, inventory, supply and dollar projections, thereby providing the business with a consistent planning process and a single set of numbers across the organization.

Did you ever wonder how the solution for slow selling products came from?  It came from Small Data (a data point from a single person).

The story goes like this. The architect of the solution was talking about planning at store level with a retail store manager in Canada, when the manager proclaimed the following, “I have no idea when these products will sell, all I know is that I’ll sell about 2 every quarter”.

Boom!

And the idea for integer forecasting and forecasting using different planning horizons (e.g., weekly, monthly, quarterly) was planted. Eventually this nugget of Small Data would be parlayed into the world’s leading and, to date, best solution for planning slow and very slow selling products at store level.

The architect of the slow selling solution didn’t get all sorts of slow selling data and then slice and dice the data to try to uncover a solution. Had he tried that approach, he’d likely still be working on it – just like most technology firms and academics.

When it comes to planning slow selling products, we owe Small Data some thanks:

First, Ken for the small data insight.

And then, Darryl for turning insight to solution.

Only a few

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Flowcasting has often been referred to as ‘the Holy Grail’ of demand driven supply chain planning (and rightly so). Driving the entire supply chain across multiple enterprises from sales at the store shelf right back to the factory.

So is Flowcasting a retail solution or a manufacturing solution? Many analysts, consultants and solution providers have been positioning Flowcasting as a solution for manufacturers.

They’re wrong.

While it’s true that some manufacturers have achieved success in using data from retailers to help improve and stabilize their production schedule, the simple fact is that manufacturers can’t achieve huge benefits from Flowcasting until they are planning a critical mass of retail stores and DCs where their products are sold and distributed.

For a large CPG manufacturer, this means collecting data and planning demand and supply across tens of thousands of stores across multiple retail organizations, all of which have their own ways of managing their internal processes.

At the end of the day, a manufacturer initiated Flowcasting implementation results in what amounts to a decision support/reporting system that isn’t directly integrated to the actual product movements that will occur from the factory to the store shelf.

Flowcasting is a retail solution that will greatly benefit manufacturers over time as more and more of their retailer customers adopt the concept.

Flowcasting is not a data collection and calculation exercise. It’s a planning philosophy that requires the folks on the front end of the supply chain (retailers) to change most of their business practices to be forward looking, such as:

  • Assortment planning and line review (including planogram resets)
  • Seasonal planning
  • Promotions planning
  • Network realignments (including store-to-DC network mappings and changes of source)

The retailer holds complete control over all of the above decisions. To the extent that they can change their processes to plan these activities in advance (and share those plans with manufacturers in a language they can understand), everyone in the supply chain benefits.

To the extent that folks on the back end of the supply chain (manufacturers) attempt to ‘work around’ retailer customers who are not thinking or operating in a time-phased manner, we are still left with a disconnected supply chain (perhaps with fancier tools).

You can’t push a rope, as they say.

The perception that Flowcasting is a manufacturing solution has led many people to conclude that Flowcasting is really applicable to only a few companies. If that perception were true, then the conclusion would be correct – but it’s not.

When we conceived of Flowcasting, we were really outlining the concept of totally integrating a retail supply chain – from point of consumption (consumers) to point of origin (the manufacturer’s manufacturers).  I believe it’s why we called the book “Flowcasting the Retail Supply Chain”.

Now, the last time I checked there were more than only a few retailers.

Does Flowcasting apply to virtually every retailer?  I believe it does.  After all, don’t they sell products to consumers using physical stores, virtual stores, or a combination of both and supply those products via a network of distribution points?  Couldn’t that be Flowcasted?  Shouldn’t it be?

Our retail client in Winnipeg Canada is managing their entire business driven by a forecast of consumer demand, by item, by store (including web store), and translating those forecasts into the demand, supply, capacity and financial requirements for a 52 week planning horizon – including sharing purchase projections with their suppliers.

They have implemented and are doing what’s outlined in our book.  They are Flowcasting.

Another misconception about Flowcasting is that all of the data must be in one place and being used by planners from both the retailer and manufacturer organizations. While this is an admirable (and likely achievable) goal, the Flowcasting planning process can be (and has been) achieved without it.

Flowcasting is about seamlessly integrating the entire retail supply chain from one forecast and working a common plan and a single set of numbers. Can and should a retailer manage their business this way?  Without question and our retail client has proven it.

The point is that separate companies can be using the same numbers and executing the same plan without logging into the same system. We need to collectively get a grip on this and learn to determine the difference between what’s cake and what’s icing (and in this particular case, a few sprinkles on top of the icing).

To extend the thinking of Flowcasting even further, consider Flowcasting as a concept and a philosophy.  A philosophy to drive the entire, integrated supply chain from a forecast at the point of consumption.

A couple of years ago, I had the pleasure to visit One Network Enterprises at their Dallas headquarters to talk about supply chain planning.  Inevitably we got talking about Flowcasting.

During the conversations, Aaron Pittman and Richard Dean proclaimed to me that Flowcasting, as a concept, had widespread application.  They insisted that the concept of driving a supply chain from point of consumption to point of origin applied to any industrial supply chain.

If you think about it, they are right.

Had we spoken to them before we wrote the book, undoubtedly we would have more aptly named it “Flowcasting the Supply Chain”.

So if you think the concept of Flowcasting applies to only a few companies…you’re right…Flowcasting does apply to only a few…

Only a few thousand!

Flowcasting the…

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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, Romeo and Juliet

It’s hard to believe that nearly 10 years have gone by since Flowcasting the Retail Supply Chain was first published. Mike, Andre and I had the manuscript nearly complete before we turned our attention to figuring out the title. I figured it would end up being something boring like ‘Retail Resource Planning’.

Then, Andre got us both on a conference call to tell us that he came up with a title for the book: ‘Flowcasting’. For reasons I can no longer remember (or maybe perhaps because it wasn’t my idea), I immediately disliked it. We went back and forth on it for awhile and as time went on, the name ‘Flowcasting’ grew on me.

Then I came up with the idea that we should be more descriptive about the process. It’s a new concept for managing the retail supply chain, right? So, we should call the book ‘Flowcasting the Retail Supply Chain’!

Now I wish I had just listened to Andre and left well enough alone.

Over the years, we’ve written and talked at length about the types of major changes a process like Flowcasting brings about in the supply chain areas for retailers and their trading partners:

  • Managing all supply chain resources (inventory, labour, capacities and spend) using a single set of numbers based on a forecast of consumer demand at the shelf
  • Collapsing lead times between retailers and their trading partners by unlocking the power of the Supplier Schedule
  • Improving supply chain operational performance by providing 52 weeks of future visibility from the store shelf back to the factory and giving manufacturers the opportunity to shift their operations from ‘make to stock’ to ‘make to order’
  • And so on and so forth

To be sure, the supply chain operational and planning changes are significant – but that’s just the beginning. To make Flowcasting successful, the mindset changes in other areas of the retail organization can be just as revolutionary.

The Merchandising Organization

Historically, the buyers in a retail organization were (and in most cases still are) just that: ‘people who buy stuff’. Their primary accountability is growing sales in their categories, and the conventional wisdom is that the best way to increase sales is to have a lot of inventory. If you think you’re going to sell 10,000 units on an ad, then you buy 20,000.

Flowcasting turns this notion on its head. Because it is always accounting for all inventories in the supply chain and replanning every day based on the sales forecast, ‘Buyers’ must learn to become ‘Category Managers’ who focus on their key accountability: generating demand and providing input to the sales forecast. The change management implications of this change cannot be overstated, as this can be viewed as taking away their control of a key input to their overall success.

Similarly, buyers are accountable for maximizing gross margin on their lines. When negotiating case packs and ordering minimums, they may be inclined to choose the option that gets them the lowest overall cost per unit. But this can be very costly to the business overall if these constraints make it impossible to flow product to the store shelf, particularly for lower sales volume stores. High gross margin doesn’t necessarily equate to high profitability for the business as a whole if folks in the merchandising organization haven’t been given the tools and accountability to think holistically about the supply chain.

Store Operations

Two decades ago, the retail supply chain was distribution centres and trucks. A few years ago, the thinking began to evolve to include the retail store as part of the supply chain. Now, we are finally starting to think of the supply chain as linking the factory to the customer’s hands.

Most retailers measure store ‘in stock’, but what’s meaningful to the customer is on shelf availability (meaning that if a store has 10 units in inventory, but it’s stuck in the back room somewhere, it’s an ‘in stock success’, but a failure to the customer).

One of the biggest questions retailers face is ‘How much autonomy do we give to the store?’ While it’s true that each individual store is closer to the market they serve than the folks at home office, does this mean that giving every store manager a stock ordering screen to use at their discretion will automatically increase customer service? In my experience, the only things it increases with regularity is inventory and confusion.

Even though Flowcasting would generally be a centrally managed process for most retailers, it’s driven from individual store level sales patterns and constraints that may not be known to a store manager. The entire process works much better when people are accountable and measured only for the things that are within their control. For a retail store, that means two things:

  • Receive the product quickly and get it straight to the shelf
  • Keep the inventory records accurate

If stores are focusing their energy in these areas, it doesn’t guarantee perfect on shelf availability for the customer, but it makes it easier to trace back where the process is failing and make corrections when there are fewer fingers in the pie.

Human Resources

Flowcasting isn’t just a different calculation for coming up with an order recommendation. It’s a fundamentally different way of operating a retail business. As such, it requires a different skill set and mindset to manage it.

While it might be tempting to fill an open replenishment position with someone with replenishment experience at another organization, you could be trying to fit a square peg in a round hole if her prior experience is with traditional reorder point or push methods. In fact, you may have to invest more time with ‘untraining’ than you do with training.

To be successful with Flowcasting, a person needs to be organized and possess decent problem solving skills. Other than that, no specific ‘experience’ is required – in point of fact, it could actually prove to be a detriment.

The Biggest Mistake You’ll Ever Make

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You must learn from the mistakes of others. You can’t possibly make them all yourself. – Sam Levenson

bridge

‘How does it work today?’

It’s the first question any self respecting project leader or consultant asks on day 1 of a new initiative. It’s critically important to know the ‘state of the nation’ before you embark on any sort of effort to make the changes needed to improve results.

After asking this question, you set about the task of learning the current practices and procedures and documenting everything to a fairly low level of detail (along with the most common variations on those practices that you’ll almost always find in companies of any size).

In most retail organizations, you’ll hear versions of the following:

  • For non-promoted periods, our purchasing is mostly automated with a short lead time, but we buy promotions manually with a longer lead time from the vendor.
  • Our stores ‘pull’ product in non-promoted weeks, but for big events like promotions and shelf resets, we ‘push’ the product out to them .
  • The system will recommend orders, but our analysts review all of the recommendations beforehand and have the ability to cancel or modify them before they go out to the suppliers.

After a few weeks, you’ve become a pseudo expert on the current state landscape and have everything documented. Now it’s time to turn this retailer from a reactionary firefighter into a consumer driven enterprise.

And that’s when you make the biggest mistake of your life.

After summarizing all the current state practices with bullet points, you save the document with the title ‘Future State Requirements’. You don’t know it at the time, but you’ve just signed yourself up for years of hell with no light at the end of the tunnel. If it’s any consolation, you’re definitely not alone.

Common practices, whether within your organization or throughout your industry as a whole, represent ‘the way everybody does it’. This does not equate with ‘that’s the only way it can be done.’

At the time, it seems like the path of least resistance: We’ll try to do this in such a way that we don’t disrupt people’s current way of doing things, so they will more easily adopt the future state. But if you’re moving from a ‘reactive firefighting’ current state to a ‘demand driven’ future state, then disruption cannot be avoided. You might as well embrace that fact early, rather than spending years of time and millions of over-budget dollars trying to fit a square peg in a round hole.

So how could such a catastrophe be avoided? All you really need to do is dig a little deeper on the ‘common practices’. The practices themselves shouldn’t be considered requirements, but their reason for existing should. For example, look at the three ‘common practices’ I mentioned above:

‘For non-promoted periods, our purchasing is mostly automated with a short lead time, but we buy promotions manually with a longer lead time from the vendor.’

Why does this practice exist? Because, generally speaking, the sales volume (and corresponding order volume from the vendor) for a promoted week can be several times higher than a non-promoted week.

So what’s the actual requirement? The vendor needs visibility to these requirements further in advance to make sure they’re prepared for it. Cutting promotional orders in advance is the currently accepted way of skinning that cat – but it’s by no means the only way.

‘Our stores ‘pull’ product in non-promoted weeks, but for big events like promotions and shelf resets, we ‘push’ the product out to them.’

Why does this practice exist? More often than not, it’s because the current processes and systems currently in place treat ‘regular planning’ and ‘promotion planning’ as distinct and unrelated processes.

What’s the actual requirement? To plan all consumer demand in an integrated fashion, such that the forecast for any item at any location represents what we truly think will sell, inclusive of all known future events such as promotions.

‘The system will recommend orders, but our analysts review all of the recommendations beforehand and have the ability to cancel or modify them before they go out to the suppliers.’

Why does this practice exist? Usually, it’s because the final order out to the supplier is the only ‘control lever’ available to the analyst.

What’s the actual requirement? To be able to exert control over the plan (items, locations, dates and quantities) that leads to order creation, allowing the actual ordering step to be an administrative ‘non event’.

So, once you’ve identified the true requirements, what’s next?  A lot of hard work. Just from the 3 examples above, you can see that there are several change management challenges ahead. But at least it’s hard work that you can see and plan for ahead of time.

Woe to those who choose what they think is the easy path at the outset only to suffer the death of a thousand surprises after it’s far too late.

 

Making the Change

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Check out the big news from JDA on their next generation Flowcasting solution. Being able to plan for slow moving SKUs using the same process as fast moving SKUs is ENORMOUS.

Toward the bottom of that press release is a link to a great whitepaper by ChainLink research called ‘Making the Change: Overcoming Obstacles and Myths in Adopting Flowcasting‘. A simple signup is all that’s needed to get your hands on it (as well as other great content). Highly recommended reading.

Technology Havens from the Storm

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Recently, Bill Belt (a Paris-based supply chain educator and consultant, not to mention a big proponent of Flowcasting), published a newsletter discussing 6 of the most transformative supply chain technology concepts dating back to the introduction of Lean Manufacturing at Toyota in the 1950s. He also lists what he considers to be the best book for each.

I think you see we’re I’m going with this. Read the English translation here. Or, if you prefer, he also publishes it en Francais.

 

Flowcasting – Easy as Riding a Bike

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Flowcasting – it’s simple, intuitive and makes perfect sense. At conferences, talks and seminars, I have yet to meet anyone who doesn’t describe it this way after learning about it.

But how easy is it for a retail planner (who has been living in a reorder point world for years) to internalize it?

Understanding the mechanics of it is very easy. And for newbies who have nothing to “unlearn”, internalizing it is a piece of cake too. But for those who have to break old habits, it’s no picnic. And even once they do “see the light”, it’s still incredibly easy to fall back into the old habits if they’re not vigilant and disciplined.

It’s kinda like this:

In Praise of Non-Collaboration

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gears

 According to dictionary.com, the definition of ‘collaborate’ is: ‘to work, one with another; cooperate’.

Recently, I received an email from Supply Chain Digest asking me to participate in a survey called ‘The State of Retail and Vendor Supply Chain Relations 2015’ – perhaps you received it too. (As a consultant, I never participate in these surveys as I feel it could taint the results, but I’m always interested in what they’re trying to find out).

The Research Summary reads: ‘What is the state of retailer and vendor/supplier relations today? Is it getting better and more collaborative – or heading the other way?’ The implication is crystal clear: More Collaboration = Better.

It seems foolish to argue against that. But that’s just what I’m going to do.

Over the years, supply chain collaboration initiatives were conceived with the notion that ‘two heads are better than one’, especially when there’s uncertainty afoot that could cause havoc in the supply chain, such as for promotions or product launches.

And because trading partners’ planning processes weren’t integrated with a common set of numbers, collaboration was seen as the way to bridge the gap (i.e. ‘we have two sets of plans that are misaligned, so let’s talk our way through it until we agree’). But to what extent is collaboration necessary (or even advisable) when trading partners are fully integrated?

Collaboration is work. Integration is effortless.

All that said, I would tend to agree with the ‘two heads’ argument, so long as all available information is shared between the ‘heads’ This is rarely the case, however, and it’s most often the result of inability to share, rather than unwillingness to share.

Consider a common scenario whereby a retailer and a supplier collaborate on a sales forecast. In order for the demand picture to be complete, the following information must be known and disclosed during the collaboration:

  1. Pricing and promotion strategy for the supplier’s products at the retailer’s stores
  2. Pricing and promotion strategy for the supplier’s competitors’ products at the retailer’s stores
  3. Pricing and promotion strategy for the supplier’s products at the retailer’s competitors’ stores

Point 1 is generally already known by both parties. Points 2 & 3 are at best, unethical (and at worst illegal) for either party to share with the other.

It’s sort of like having two people collaborate on what bet to place on a 5 card poker hand. Each person can only see 3 of the 5 cards with one common known card between them and they aren’t allowed to discuss the cards they can see with their collaboration partner. But the strength of the hand is determined by all 5 cards together.

As a general rule, the retailer faces the customer and they know the breadth of their offerings across all of their competing and complementary products. They may not know exactly what their competitors are doing that could impact their sales, but they pretty much know everything else. Given that the supplier is ethically prevented from providing the one missing piece of information, what value do they add to the collaboration process?

Another example is collaboration on network efficiency to alleviate capacity issues at retail DCs during peak periods. The problem here is that a capacity constraint occurs as a result of a number of straws breaking the camel’s back. Only the retailer has the visibility to all of the straws. How can a collaboration with any single supplier (straw) result in a plan to smooth out the flow for the entire building?

Note that I’m not suggesting that retailers and suppliers shouldn’t be talking to each other when circumstances require it. In the capacity constraint example, the retailer has all the information they need to detect the constraint and figure out the best way to circumvent it. At that point, discussions may need to happen with some suppliers to pull shipments ahead or maybe bypass nodes in the supply chain, but at that point, they’re really just working out execution details rather than ‘collaborating on the plan’.

When you think about it, the supply chain is really not a chain at all – it’s a web. With the exception of private label goods or exclusive supply arrangements, the notion that a retailer and a supplier can ‘act as a single entity in service to the consumer’ is not as easy as it sounds – even with advanced planning processes like Flowcasting. Each retailer offers products from many competing suppliers and each supplier provides their products to many competing retailers.

So if the idea of collaboration is somewhat flawed, then what is better?

Basically, retailers need to get their houses in order and build all of their planning activities around sales at the store shelf (using Flowcasting, of course), incorporating all information they know into the plan – inventories, shipping/receiving schedules, case pack sizes and the like.

Once constructed by the retailer, these plans can be shared directly with suppliers, allowing them to ‘read the retailer’s mind’ without having to second guess or do a lot of ‘collaborating’ back and forth. Discussions between business partners only need to occur when either party foresees difficulty in executing the plan.

Why collaborate when you can integrate?

The Inkblot

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Philosophers have only interpreted the world, in various ways. The point, however, is to change it. – Karl Marx (1818-1883)

What do you see when you look at the image above? A demon skull? An old woman with wild hair? A happening dance party?

That’s the great thing about the Rorschach inkblot test – there’s no wrong answer. Any and all interpretations of an inkblot are “right”.

In many ways, a lot of what have been considered to be key supply chain advances are often treated in the same way. Over the years, I’ve met many people at conferences and seminars who proudly state that “we’re doing CPFR” or “we’re doing S&OP”. After short conversations with these folks, it seems that the definition of “CPFR” and “S&OP” has become somewhat diluted. It seems that any time someone shares a spreadsheet with someone outside their organization, it’s “CPFR” and whenever two people from different areas of an organization are in the same room, it’s “an S&OP meeting”.

Part of this is because these terms have successfully pervaded the supply chain lexicon and are well known. People are either jumping aboard a bandwagon or perhaps unintentionally using the terms as shorthand for something they were never meant to convey.

However, to a certain extent, these concepts sort of had it coming. While the early proponents and practitioners of these concepts laid out some guidelines and principles, there was still a lot of grey area as to how they could be applied to the actual day-to-day operation of a business by the people who actually run the day-to-day business (hint: those people do not occupy the executive suites).

Whenever I speak about Flowcasting, there are inevitably people who come up to me afterward to tell me “we’re basically doing Flowcasting in our company right now!”

I hate that word “basically”.

However, my interest is always piqued when I hear this, so I press for more information. Here are some “flavours” that I’ve heard over the years:

– “We have 52 week time-phased plans at our stores feeding back to the DCs but only for a selection of items.”

– “We do time-phased planning for all of our items in all of our stores and DCs, but they aren’t connected to each other.”

– “We have plans connecting all stores to all DCs for all items, but only over the next 13 weeks.”

– “We use multi-echelon planning for our regular volume, but we have a separate push process for promotions.”

I don’t know what the names of each of these variations might be, but the stuff after the “but” means that it is definitely not Flowcasting.

Flowcasting only works as a sum of all its parts and you can’t pick and choose criteria from a menu and label it “basically Flowcasting”, any more than you can say that any object with 4 wheels on it is “basically a Ferrari”.

So how can you know if you’re truly “doing Flowcasting” without having to read a 300 page book on the subject? Fortunately, the Flowcasting process is detailed and specific, without much room for a lot of “eye of the beholder” stuff.

If all of the following are true, I think you can reasonably claim that you are part of a Flowcasting organization:

– If someone chooses any item in your assortment, any location in your network and any day in the upcoming year, you can enter these 3 pieces of information into a system and it will tell you what your sales, receipts and on hand balance will be for that item in that location on that day.

– For any item at any selling location, you can see a 52 week sales forecast that incorporates all known future demand influences, including seasons and promotions.

– Except in rare cases, all orders and stock transfers are administrative “non events” that trigger automatically with a single lead-time and without any human intervention. Yes, that goes for promo orders too.

– You can view any location in your network and you can see inbound, outbound and inventoried cubic feet, weight, pallet positions, picks, receipts and labour hours for any day in the next 52 weeks – and you can drill down to see precisely which items are driving those high level metrics on that day.

– You can automatically create a financial plan for any item, category or across the entire business for the next 52 weeks, including sales, purchases and inventory investments. Then you can update the forecast for one item and the financial plan at any level automatically refreshes.

You may not be able to get there overnight, but once you’re there, you are Flowcasting. Basically.

Okay, rant over.