Flipping your thinking

When students at Segerstrom High School in California attend calculus class, they’ve already learned the day’s lesson beforehand — having watched it on a short online video prepared by their teacher, the night before.

So without a lecture delivered by a teacher, students spend class time doing practice problems in small groups, taking snap quizzes, explaining concepts to the class, and sometimes making their own videos while the teacher moves from student to student to help kids who are having problems.

It’s a new form of learning called Flip – because the idea has flipped traditional education on its head – homework is for the lecture, while the classroom, traditionally reserved for the lecture, is for practice and deeper learning and collaboration.

Flipped learning is catching on in a number of schools across North America, as a younger, more tech-savvy student population – including teachers – now make up the typical classroom.

When it comes to supply chain planning, the concept of flipping applies nicely and most people, and most companies, could benefit greatly by flipping their thinking.

Let’s take CPG manufacturers.  When it comes to demand planning, they have it difficult.  Trying to forecast what their retail and other customers are going to do and want is difficult and it’s not getting any easier.  The empowered consumer, changing and dynamic retailer-led strategies are just two examples of shifts that are making it almost impossible to predict the demand, with any level of reasonableness.  The result?  Additional inventory and buffer stock required to respond, “just in case”.

There are a number of studies that prove this point.  Forecast accuracy has not improved and, in most cases, it’s getting worse.

Supply chain practitioners and experts are responding in the typical fashion.  We need better algorithms, fancier formulas, maybe even artificial intelligence and some big data sprinkled on top in order to find a better forecasting engine.

Sorry folks, that’s not working and as consumers and customers become more demanding and expectations rise, it’s going to get worse.  What’s needed is to flip the thinking and to change the paradigm.

CPG manufacturers, for the most part, are forecasting what should be calculated.  The demand plan they are trying to predict for their customer, should be provided to them in the form of a supplier schedule.  And that schedule should reflect the latest knowledge about the consumer, and any and all associated strategies and tactics that will entice the consumer’s buying patterns and/or product flows.

Forecasting consumer demand is, as has been proven, simpler and easier that trying to predict dependent demand – that is, the resulting demand on DC’s and plants based on ordering rules, lead times, and other constraints that tend to “pollute” the dependent demand plan.

When it comes to demand planning, Joe Orlicky had it right some 40 years ago: you should never forecast what can be calculated.

Of course, what we’re talking about is a retailer using the Flowcasting process to plan all flows from supplier to consumer – factoring in any and all constraints that translate the consumer forecast into the purchase projection from retailer to supplier.

Why is this so much better than the traditional approaches?  First, the entire retail supply chain (or any industrial supply chain) is driven by only one forecast – consumer demand.  All other demands can and should be calculated.  The effect is to dramatically simplify planning.  The retailer and manufacturer are working to a single, shared forecast of what’s expected to sell.

Second, the entire supply chain can be re-planned quickly and effortlessly – making the supply chain agile and dynamic.  Changes are and can be viewed almost in real-time and the changes are automatically translated for all partners in the supply chain – in units, cube, weight, dollars, capacity or any language needed throughout the supply chain.  The result is that the entire supply chain is working to a single set of numbers.

Third, when you embrace the idea of Flowcasting as it relates to planning, you get so much more than a better forecast.  Unlike traditional approaches that are trying to mathematically predict the demand, the supplier schedules that are a resultant of the Flowcasting process, calculate the demand by aggregating product flows.

Therefore, trading partners can see, well into the future, projected product flows between any two locations and this provides tremendous insight and flexibility to improve and smooth flows, as well as proactively put in place solutions to potential flow issues before they happen.  The retailer and manufacturer can actually work, using the same system and process, as if they were one company – all oriented to delight and deliver to the consumer, in the most profitable manner possible.

Finally, in addition to providing product flows the approach also produces projections of sales, inventory, purchases, receipts and, as mentioned, flows in any language of the business – units, cube, weight and capacities for operations folks and dollars for financial folks and Management in order to get better control of the business and ensure that plans stay on track.

If you’re planning the retail supply chain, you get so much more when you forecast less.

So, what is the path forward for manufacturers?

They need to flip their thinking and understand that they are trying to forecast what should be calculated – and that this practice will soon be obsolete.

Next, they should engage and work with their key retail and other customers to help educate their customers that a process like Flowcasting not only helps them (in the form of a supplier schedule and complete visibility), it provides even more value to the retail customer.  In fact, to date, it’s the only planning approach that consistently delivers in-stock levels of 98%+, even during promotions – crushing the industry averages of around 92%.

Once they are successful, a CPG manufacturer, over time, can be working with their top retail customers and receiving valid, up-to-date, supplier schedules that in most companies account for 70-85% of their volume.  The additional demands can then be forecasted using the latest approaches – demand sensing, etc.

Imagine, for a moment, what that would mean to the retail industry and the CPG manufacturers in general.  The impact would be enormous – from increased sales and profits, to significant reductions in inventory and working capital.  Not to mention the impact to consumers and customer loyalty.

Is all this possible?

Sure, but to make it happen the first step is to flip your thinking.

Prototyping the prototype

If someone asked me to summarize myself, I’d probably say that I’m a life-long student – an avid reader and someone who knows that things can always be made better – a lot better.

Some recent experiences have got me thinking about our approach to designing and implementing Flowcasting-like solutions for our clients.

First, what has made our approach so successful?  It’s really an obsession with simplicity and a deep understanding that instilling new behaviors is about people and process.

At the heart of the approach is what we call a process lab, or process prototype.

Think about how successful products are created.  They are designed.  Then a prototype is created.  Then it’s tested.  Then it’s revised.  Prototyped again.  Tested again, and the process continues until the product sees the light of day.

Why can’t a process change also be prototyped?

It can and we do.

We work with teams to design new processes and workflows on paper then build a lab-like environment and prototype the process with real end-users.  It helps people see and feel the process first-hand, and also provides us critical early feedback on the process – how it works, what people like, what they struggle with, where it can be improved, etc.

It’s all consistent with our belief about change – that people rarely believe what you tell them, but they always believe what they tell themselves.

On our recent implementation of Flowcasting for a hard goods retailer in Western Canada, I was fortunate to experience what could be described as rapid prototyping, with respect to the technology solution.

To set the stage, the Flowcasting solution we used was an early and immature solution.  However, the fundamental foundation and architecture, along with the retail focused functionality was second to none.

Of course, even though we designed and did our prototype lab work with the team and users, a number of things emerged that we needed to revisit as we made the journey.  As luck would have it, we were working with the actual architect of the solution and, over a couple of months, we made some important and elegant revisions to the solution that improved it considerably.

Essentially we did a series of small, software-focused prototypes (to support our process thinking, of course) that were quickly designed, tested then deployed.  It was one of the most exhilarating experiences I’ve been involved in and I’ve been doing project work since the dawn of civilization (at least it feels like that!).

The result was equally impressive.  Even though the RedPrairie Collaborative Flowcasting solution was already an excellent one, the changes that were prototyped and implemented transformed the solution into something special and unique.

In my professional and expert opinion the solution solves all the major retail planning challenges, is intuitive, scales like stink on a monkey and is so simple that even an adult can learn and use it.  Even. An. Adult.

Not long after this experience I read an interesting book called Scrum – about an approach for designing and implementing new technologies that relied on rapid prototyping.  The basic idea was to design things quickly, make the changes, test it and demonstrate it to people and adjust accordingly.  Then rinse and repeat.

Boom!  It was essentially the approach that we’d used so successfully to transform the Flowcasting solution.  And, it got me pondering.

Why wouldn’t we apply the same thinking to our implementation framework?  After all, the idea of a process prototype was not foreign to us – in fact, it’s a cornerstone of our approach.

Perhaps we should do more than one…just like this:

Prototype picture

The idea would be to do shorter bursts of design and lab work, then engage the users, get them to work with the process, and provide feedback and adjust.  I have no idea how many of these micro-prototypes we might need but the approach could be flexible to have as many as required – depending on the magnitude and scope of the change.

I really like the idea and hopefully will test it soon.  We’re working with a great bunch of folks at a Canadian retailer and hopefully we’ll get the opportunity to help them with the implementation.  If that happens, I’m sure we can leverage this thinking and incorporate it into our approach.

It will be like prototyping the prototype.

Saying No

The folks that know me well, understand that I’m a pretty humble guy.  Today I’m going to toot my own horn a little, and share my deepest, closely guarded secret.  If bragging and self-indulgence offend you, then I suggest switching to a different channel.

I’ve had the good fortune to have led two of the most important and foundational planning implementations in retail.  I’ll give you a little background on each, then follow with what I believe are the secrets of success.

First up: Canadian Tire in the mid to late 1990’s.    While the design was essentially what we now call Flowcasting, the implementation focused on the introduction of integrated, time-phased planning from DC to suppliers and linking and collaborating with 1500+ suppliers who, to this day, receive a rolling 39-week projection of planned product purchases.

The implementation was a first in a couple of key areas.  It was the first complete implementation of DRP (Distribution Resource Planning) in retail and also the first widespread use and adoption of supplier scheduling across a retail vendor base.

The solution deployed was Manugistics (now part of JDA) and was also a very early implementation of client-server technology.

The implementation was very successful – improving a number of key metrics like service levels, inventory turns and supplier lead time and delivery performance.

The second implementation was the recently completed implementation of the Flowcasting process at Princess Auto Ltd.  This implementation is a world first.  They are the first retailer to plan their entire, integrated supply chain based on a forecast of consumer demand.  The business is being managed using a single set of numbers and they have achieved the vision outlined in our book (http://www.flowcastingbook.com/).

In terms of results, store in-stock has risen nicely and they consistently have store in-stocks of 97%+, even for promoted products.  Inventories are more productive and the entire business is using the Flowcasting projections to manage to a single set of numbers.

The solution deployed was the Collaborative Flowcasting solution, a joint venture with RedPraire and the Retail Pipeline Integration Group, now also part of JDA.

Obviously, I’m pretty proud of these implementations. While there are a number of things we could have improved upon during the implementations, these two implementations have pushed the thinking and practice of retail supply chain planning and integration.

Now, lean in, real close, for I’m about to share the real secrets of success.

The success of these implementations is a direct result of being able to say…   No.

Great innovations and implementations are, in my opinion, largely a result of being able to say no to suggestions and ideas that don’t support the vision.  Steve Jobs described it as “saying no to a thousand things”.

The same principle applies in supply chain planning and especially the introduction of supporting technologies.

My approach is to build simple designs and only use technology and code where a computer algorithm can do a better job than a human.  Instead of trying to algorithm our way to greatness, the focus is on changing the process and thinking rather than changing computer code.

For example, in my Flowcasting world, I would never allow us to go down the path of ordering product from a supplier at two different lead times – one for regular and one for promotional volumes.   I have consistently said no to this inevitable request – instead, helping the design team understand the complexity of this thinking and, then orienting them to educate and work with suppliers so they can plan and deliver to a single lead time.

This, of course, is just one of many situations where I happily get to say No.  Over time, people begin to realize the impact of saying yes to everything…the design and solution is too cumbersome, too heavy, hard to implement and manage and often collapses under its own weight.

Now, of course I’m not saying to say No to everything suggested.  Usually the suggestions are grounded in decent thinking and needs.  The art is to understand what people need and to deliver the needs, but not necessarily in the manner they have suggested – which, inevitably they do.

Imagine if planning system architects subscribed to the Doherty/Jobs doctrine?

We’d have elegant, simple and intuitive planning solutions – not the complicated, rigid solutions that tend to dominate the market today.

One notable exception was the Flowcasting solution we used during the Princess Auto implementation.  It’s a solution that was designed for Flowcasting from the store/shelf and the architect is also a master at “saying no to a thousand things”.

As a proof point, the initial implementation of the Flowcasting solution was rolled out company-wide using a single business consultant (yours truly) and less than a third of one person’s time from the technology provider, in an elapsed time of 18 months.

Furthermore, the solution was cloud-based and integrated with their existing ERP system using 5 simple integration points (i.e., interfaces) and with No customizations and No system workarounds.

There’s that word No again.

It really is the secret to success.

At least mine.

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

 

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

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

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…

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

 

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

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‘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

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

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.