Virtual Reality for the Retail Supply Chain

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Whenever we discuss Flowcasting, we always describe it as ‘a valid simulation of reality inside a system’. This term originated with our longtime colleague Darryl Landvater and it is the most concise and accurate way to describe what Flowcasting really is that we’ve heard.

In fact, we use that term so much that I think we sometimes assume its meaning is self evident.

It’s not.

Over the last 11 years since Flowcasting the Retail Supply Chain was first published, I’ve noticed that, more and more, the terms ‘Flowcasting’ and ‘valid simulation of reality’ have been treated somewhat like ink blots, with some folks (intentionally or otherwise) using them to mean whatever they want them to mean.

To set the record straight, a true ‘valid simulation of reality’ for the retail supply chain has some very specific characteristics, all of which must be present. To the extent that they are not, the value of the plan suffers – as do the results.

Before diving into the nitty gritty details, consider this: Virtually all retailers have a data warehouse that captures daily sales summaries for every product in every location, all upstream product movements, every on hand balance and certain attributes of every product and every location. This data is usually archived over several years and the elemental level of information is kept intact so that rollups, reports and analysis of that data can be trusted and flexibly done.

Think of a valid simulation of reality for the retail supply chain as a data warehouse – with a complete set of the exact same data elements at the same granular level of detail – except that all of the dates are in the future instead of the past.

However, it must also be said that ‘valid’ does not mean ‘perfect’. Unlike the historical data warehouse that remains fixed after each day goes into the books, the future simulation can and will change over time based on what happened yesterday and new assumptions about the future. Updating the simulation daily at all levels is the key to ensuring it remains valid.

Now let’s get into some of the specifics. A valid simulation of reality has 4 dimensions:

  • Information about the physical world as of this moment
  • Forecasts of expected demand over the next 52 weeks for each individual product at each individual point of consumption (could be a retail store or a virtual store)
  • A simulation of future product movements driven by the forecasts and future planned changes to the physical world
  • Rollups of the elemental data to support aggregate planning in the future

While it may seem that meeting all of these requirements is onerous, it is actually quite simple compared to trying to do things several different ways to account for variations in how products sell or are replenished.

Current information about the physical world includes things like:

  • Master information about products (e.g. cube, weight, pricing, case packs, introduction and discontinuation dates) and locations (stores, DCs, supplier ship points)
  • Relatively accurate on hand balances
  • Planogram details such as store assortment, facings and depth
  • Source to destination relationships with lead-times that are representative of physical activity and travel times

This information is ‘table stakes’ for getting to a valid simulation of the future and is readily available for most retailers. High levels of accuracy for these items (even store on hands) is achievable – so long as the processes that create this information have some discipline – because they are directly observable in the here and now.

Forecasts of demand over the next 52 weeks must:

  • Include every item at every selling point
  • Model demand realistically for slow selling items (i.e. integer values as opposed to small decimals that will model an inventory ‘sawtooth’ that won’t actually happen)
  • Include all known positive and negative future influences for each individual item at each individual selling location (e.g. promotions, assortment changes, trends)
  • Allow for ‘uncertainty on the high side’ for promotions to be modeled independently from the true sales expectation so as not to bias the forecast, especially for promotions
  • Account for periods where inventory is planned to be unavailable at store level (e.g. sales forecast for a discontinued item should continue while the item is in stock and drop to zero when it’s projected to run out in the future)

The rule here is simple: if the item at a location is selling (no matter how slowly or for how long) it must have a sales forecast and that sales forecast must be an unbiased and reasonable representation of what future sales will look like.

A simulation of future product movements driven by the forecasts and future planned changes to the physical world means that:

  • Replenishment and ordering constraints are respected in the plan (e.g. rounding up to case packs if that’s how product ships, rounding at lane level if truckload minimums across all products on a lane are required)
  • Activity calendars are respected (e.g. an arrival of stock is not scheduled when a location is not open for receiving, a shipment is not scheduled during known future shutdown)
  • Carryover targets are respected for seasonal items (e.g. before the season even begins, the planning logic suppresses shipments at the end of the season so as to intentionally run out of stock at the stores and DCs)
  • Future changes to stocking requirements (e.g. changing the number of facings for an item or adding/subtracting it from the store assortment) are known in advance and the effect is visible in the plan on the future day when it will take effect
  • Future changes to network and sourcing relationships (e.g. changing a group of stores to be served by a different DC starting 2 months from now) are known in advance and the effect is visible in the plan on the future day when it will take effect
  • Future price changes (whether temporary or permanent) are known in advance and the effect is visible in the plan on the future day when it will take effect
  • Pre-distributions of promotional stock are scheduled in advance to allow display setup time ahead of the sale
  • Except in rare cases, the creation and release of orders or stock transfers at any location is a fully automated, administrative ‘non event’ that requires no human intervention

Here it can be tempting to take shortcuts that seem ‘easier':

  • ‘We don’t bother forecasting or planning slow moving items at store level. We just wait for a reorder point to trigger.’
  • ‘For items we only buy once from a vendor, we just manually buy it into the DC and push it all out to the stores.’
  • ‘We know our inventory isn’t very accurate for some items at store level, so we just get the store to order those items manually based on a visual review of available stock.’

In order to have a valid simulation of reality that supports higher levels of planning beyond immediate replenishment (see next section below), you need a system and process that can model these things in a way that is representative of what is actually going to happen.

If an item/location is selling/sellable, then it must have a forecast for those sales.

There is actually no such thing as ‘push’ in retail (unless you are able to ‘push’ product into a customer’s cart against their will and get them to pay for it).

Rollups of the elemental data to support aggregate planning in the future means:

  • You can do proper capacity planning with a complete view of the future because a common process is being used at the elemental level, cube/weight data is accurate and so-called shortcuts are not being taken at the elemental level
  • S&OP is possible because the elemental plans are complete, have future pricing changes applied – instead of looking in the mirror with ‘budget vs actual’, senior leaders and decision makers can look through the windshield and compare ‘budget vs operational plan

While all of these elements that define ‘valid simulation of reality’ may seem intuitive and reasonable, it doesn’t stop some people from saying things like:

  • ‘A lot of items, especially slow movers, can’t be forecasted, so the whole idea kinda falls apart right there.’
  • ‘That’s a great theory, but it’s actually not possible to use a pull-based system for every item.’
  • ‘Just because of sheer volume, it’s impossible to manage every product at every location in this way.’

Again, as mentioned previously, a single process framework that can be used for all possible scenarios is actually much simpler to implement and maintain over the long run.

Plus, well… it’s already been done, which kinda deflates the whole ‘it’s impossible’ argument.

The EACH Supply Chain

It’s no secret that retail is undergoing some pretty big changes and will undoubtedly see even more significant shifts in the coming years. While most people are extolling the impact of digitization on retail, there is, in my opinion, a very fundamental and profound shift underway.

The shift is to the EACH supply chain.

Supply chain efficiency is about density. Filling up trucks, planes and trains. Delivering bigger orders. Driving the unit handling cost down. Makes sense and for any retailer, having a reasonable and competitive cost structure is important.

The world, however, is changing. Two major shifts are driving us towards the EACH supply chain – customer expectations and product proliferation/marketing.

Most retail supply chain professionals gained their supply chain knowledge in the world of logistics. It was about moving boxes and cases between facilities. Many, even to this day, don’t really consider the store part of the supply chain. They’ve been conditioned to be content once the product leaves a facility, destined to a store. And measures, to date, reflected that. Fill rates were measured and reported on based on if orders left a facility on time and in full.

It’s only relatively recently that retail supply chain executives began to measure store in-stock and, sometimes, on-shelf availability. Try to find a retailer that measures and reports on store inventory accuracy? It’s a tough search. Yet, having an accurate on-hand balance at store level is becoming more and more a necessity – not only to deliver an excellent customer experience but, importantly, to enable the supply chain to perform, particularly in an omni-channel world.

Retail supply chain thinking, however, needs to extend beyond the store. It needs to, and does, include the customer. The customer is now empowered – armed with finger-tip product and delivery knowledge and their expectations are on the rise.

Customers buy in EACHes, not cases – whether in store, or online and, as we all know, online volume is increasing and that trend will likely continue. Meaning, of course, that the retail supply chain needs to be re-thought and re-architected to deliver in EACH.

When omni-channel was in its infancy, many retailers set up a dedicated distribution centre (DC) to process and fulfill online orders. DC’s, however, traditionally don’t deal with EACHes very well. Combine that with the cost of home delivery and omni-channel fulfillment has been, to date, a losing proposition for most retailers.

Retailers have traditionally set their shelf configurations to hold more than a case quantity and have set their replenishment strategy such that once the on hand balance reaches a minimum level, then an additional case can be ordered to, hopefully, flow directly to and fit on the shelf.

The problem is that all these cases take up too much space and inventory and, often, the arrival of a case of a specific product results in enough inventory to last for weeks and sometimes months. What retailers are beginning to realize is that if they can flow product closer to the EACH rate in which they are demanded, more products can fit on the shelf and be available in the store for presentation to customers.

It’s hard enough for retailers to encourage and entice customers to shop in store and one way is to increase the breadth of assortment – along, of course, with making the shopping experience unique, entertaining and fun.

Marketing and advertising is also evolving to an EACH philosophy and that’s also pressuring the retail supply chain to be EACH-capable. The proliferation of mobile device ads and offers are targeted specifically to people based on data and learnings from individual consumers shopping and search habits. The result? Further demands in EACHes.

Product proliferation is also necessitating the EACH supply chain. The “endless aisle”, as it’s sometimes called, is upon us, and think about the number of possible products available for purchase from Amazon, or on the web in general – it’s staggering and, again, will only increase.

Amazon, of course, is the poster-child of the EACH supply chain. Think about what they’ve been up to over their 20 years of existence. Making online shopping as easy and seamless as possible, while slowly and steadily moving fulfillment closer and closer to the consumer – reducing times and costs in the process. Inherently they understood and have shaped the thinking towards the EACH supply chain and continue to work to reduce costs and, more importantly, cycle times and customer friction.

As customers shift more of their consumption to online this necessitates thinking and designing the flow of inventory from supply to consumer. What’s emerging as a viable model is for retailers to leverage the store to deliver to the customer – either by encouraging/rewarding for picking up in store, or by delivering from store to home.

On the planning front, Flowcasting should be considered a foundational process to facilitate and enable the EACH supply chain. Given many retailers will evolve to delivering the EACH demand from store level, then it’s logical and sensible to plan the total consumer demand from store level. Some of the sales in the store will be through the cash register, some by customer pick-up and still others by shipping from store to home.

Regardless, it’s still a sale and this sales history would be used, in aggregate, at store level to forecast future consumer demand for that store/supply point. Since Flowcasting re-forecasts and re-plans the entire supply chain daily, shifts in demand are quickly assessed, and translated into meaningful plans for all partners in the retail supply chain.

Retail and retail supply chains are undergoing massive changes. I believe that, at the heart of this transformation, is the shift to the EACH supply chain.

Of course, you may not agree and that’s cool.

After all, as the old saying goes – to EACH their own.

Secret principles of Amazon, Flowcasting

The recent acquisition of Whole Foods by Amazon has sent shock waves throughout the grocery industry and, indeed, the retail industry as a whole.  While I’m quite sure retail is not dead, as some proclaim, I’m convinced it is and will undergo massive change in the years ahead.

Early pundits and supply chain professionals were very quick to scoff at Amazon and their business model. The experts predicted that they would never make money selling things over the internet and delivering directly to your home.  And, for a number of years they were right.  However, a combination of scale, volume and innovation has disproven this, as evidenced by the chart below:

Amazon-profits

Clearly, Amazon is doing well financially and have become a profit machine.  Further evidence of the fruits of their labour can be seen in the following chart, which outlines the change in major retailer’s gross margins over the last few years:

Amazon-margins

The story of success of Amazon is not really about scale and volume to ensure their supply chain costs are competitive.  Sure, that’s important and something they continue to work on, but the success of Amazon is really built on its culture and three fundamental principles that Jeff Bezos has instilled in the organization.  In his own words, they are:

  1. Put the Customer first
  2. Invent
  3. Be patient

Customer First
Amazon, no one can deny, puts the customer first.  Think of all the innovations they have introduced and almost all of them have been designed to improve the customer experience. Bezos takes the view of the customer seriously, and rumour has it that at executive meetings sits an empty chair.

This chair is reserved for the customer. And, when they are debating ideas and concepts, Mr Bezos will turn to the empty chair and ask, “what does the customer think”?, and a customer focused discussion ensues.

Invent
The following number says it all:

Amazon-patents

That’s the number of patents that Amazon has been awarded.  Yup – one thousand, two hundred, and sixty three and counting.

Amazon is an innovation factory and, given the turbulent times and unprecedented change on the horizon, what better organizational capability to have.

If you’re competing against Amazon (and there’s a decent chance you are or will be), here’s a question: how many patents has your organization been awarded?

Be Patient
Again, you would be hard pressed to argue that Amazon is not patient.  They have also been smart and have had the good fortune of convincing their employees and shareholders to be patient as well.

They take the long view and are not driven by short term goals.  Being patient also ensures that they give the innovation machine time to work.  Change takes time.  And Amazon seems like they’ve got all the time in the world – to patiently make sure the innovation works, or they learn something from it.

These are the three principles that Jeff Bezos has believed in and instilled in the very fabric of the Amazon culture.  This is the secret to their success and is, no doubt, difficult to replicate or change an existing culture to embrace.

Parallels of Flowcasting and Amazon
The evolution of Flowcasting has, in many ways, paralleled the principles of Amazon.

Customer First – Flowcasting, as you know, is based on the tenet of “never forecast what you can calculate”, and the entire retail supply chain is driven by a forecast of consumer demand.  Flowcasting is definitely a Customer First philosophy.

Invent – Flowcasting is an innovation on how the retail supply chain works.  A single forecast of consumer demand, by item/store/selling-location can be translated into all product, financial, capacity and resource flows throughout the entire supply chain.  This is not how retailers and their trading partners have worked (or still do for virtually all of them) and is an invention in supply chain planning.

Patience – Flowcasting is only now starting to gain traction, with our client, Princess Auto, being the first retailer to implement the process properly and completely. Did you know that the idea of Flowcasting was conceived about 35 years ago, and improved upon by a small group of folks about 20 years ago?  Andre Martin and core members of the Canadian Tire team (including yours truly) have had the patience to see Flowcasting work as intended.

Ralph Waldo Emerson summed it up nicely when describing the importance of principles:

As to methods there may be a million and then some, but principles are few”.

Spot on Ralph.  Spot on.

The E-Commerce Secret Weapon

All the secrets of the world worth knowing are hiding in plain sight. – Robin Sloan

TopSecret

The end is nigh! If you still have physical stores with inventory, staff and cash registers, you’re a dinosaur and Amazon is coming to kill you! The future is online!

Okay, the rhetoric hasn’t been quite that sensational, but it wasn’t so long ago that ‘experts’ were on the verge of predicting the demise of retail as we know it.

As people (eventually) came to their senses on this, a new reality began to emerge, hidden in plain sight. It turns out that the decades of investments retailers made in their physical store footprint may not have been a complete waste of money after all. In fact, it’s actually a key competitive advantage that may result in Amazon playing some ‘catch up’ of their own in the not too distant future.

To be sure, the ‘buy online, delivery to home’ channel pioneered by Amazon represented a significant shift in how people buy goods. If you didn’t mind a bit of a wait and some extra delivery costs, you could shop without ever having to leave the house.

Over time, new products and services were added to build density, reduce shipping costs to customers and decrease delivery times for many in stock items. This could only happen cost effectively by positioning inventory closer to customers… kinda like what ‘NARs’ (‘non Amazon retailers’ – trademark pending) have been doing for decades.

For customers, that means brick and mortar retailers with an online presence can offer far more shopping and delivery options than Amazon (at least for now).

Click and Collect (or Buy Online, Pick Up in Store)

One way to look at click and collect is that it’s ‘not quite as convenient as home delivery’. In reality, click and collect isn’t necessarily a ‘convenience compromise’ in the mind of every customer – many (including yours truly) consider it to be a different (and more cost effective) kind of convenience.

This option allows customers to reserve their stock in advance and have store staff traverse the aisles on their behalf. And when customers get to the store to pick up their online order, they have the additional option to grab a few last minute or forgotten items. Or maybe they just want curbside pickup so they can get the items loaded directly into their trunk without even having to park.

And for customers who truly view click and collect as a convenience compromise vis-a-vis home delivery, Walmart now allows them to trade in some of their convenience for savings by giving them a discount for choosing click and collect over home delivery.

Third Party Personal Shoppers

This is a relatively new phenomenon, but companies like Instacart have been partnering with retailers to take orders online, shop local stores and home deliver to customers, offering cool features like chatting so that the personal shoppers can make real time decisions with the customers for substitutions or to take advantage of in store promotions.

Home Delivery from Stores

Because retailers already have inventory geographically close to customers, they have the ability to take advantage of cheaper modes of transit (i.e. ground vs air) to deliver in a 2 day time window.

But they also have the opportunity to make delivery promises in hours rather than days in their more densely populated markets, through the use of local couriers or even their own store employees.

Will all of these delivery options (plus a few others that haven’t been dreamed up yet) be popular and/or profitable? Click and collect seems like a done deal – time will tell for the others.

The point here is that these options are only available to retailers who have a retail store network in place. Far from being outmoded or passe, the ‘brick and mortar’ store network is becoming a critical linchpin in meeting customers’ online shopping expectations.

You never would have imagined it a few years ago, but the popularity of online retailing has actually served to enhance the importance of the old fashioned brick and mortar retail store rather than to diminish it. And as such, planning the supply chain from the store level back using Flowcasting becomes even more critical to a retailer’s success than ever.

 

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!