A Symphony of Placid Beauty

Game6-FinalPosition

July 23, 1972. Reykjavík, Iceland. An event would occur that day that would rock the chess world and would continue to be talked about, even to this day. It was game 6 of the acclaimed world chess championship match between the World Champion, Boris Spassky of Russia, and the challenger, Bobby Fischer of the United States.

Fischer opened 1. C4, the English Opening – the first time in his entire career that he’d deviated from his beloved 1. E4 opening move. Spassky quickly transformed the opening into the Queen’s Gambit Declined, for which he was one of the world’s foremost experts in this line of defense.

What followed was a masterpiece. Fischer’s moves were new, exciting and novel on a variation that had been played by chess grandmasters for centuries. The moves were pure, clean and deceptively simple, yet powerful and profound.

When Spassky resigned after Fischer’s 41st move, not only did the crowd stand and applaud, so too did Spassky. They all knew that they’d witnessed a masterpiece. A game of such beauty and purity – still talked about to this day, as chess perfection.

Dr Anthony Saidy, a Fischer confidant and assistant described it magically when he proclaimed, “it was like a symphony of placid beauty”.

Fischer’s play in game 6 captures his signature style: crystalline – transparent but ingenious and incredibly profound and powerful. Nigel Short, the highest ranked British Grandmaster of all time sums up Fischer’s play nicely, “The thing that strikes me about Fischer’s chess,” he says, “is that it’s very clear. There are no mysterious rook moves or obscure manoeuvrings. There’s a great deal of logic to the chess. When you look at it you can understand it – afterwards. He just makes chess look very easy.”

There are a lot of parallels to Fischer’s chess, particularly game 6 from 1972, and Flowcasting.

Flowcasting, as you know, seamlessly connects the supply chain from the consumer to the factory in a natural and logical way. That’s easy to understand and most people seem to get that.

However, like analyzing Fischer’s moves, the nuances of the process are deceptively powerful and profound. I’ll outline a couple of important ones, though there are others and they follow the Fischer-like mantra – deceptively easy to understand, simple, yet profound.

The forecasting approach used by the leading Flowcasting solutions does not use any sophisticated algorithms. Instead it uses and builds on profile based forecasting techniques that have been around for decades – the subtle improvement (like some of Fischer’s novelties in game 6) is the use of differing forecast time periods by SKU, converting them to integer forecasts for slow selling items and then consuming these forecasts as actual sales happen.

Why is that placid-like beauty? Because if you study retail, and real sales history, you’ll uncover that the vast majority of products sell less than 26 units per year per store for virtually any retailer. Trying to find a fancy algorithm that can predict when these sales will occur is a fool’s game.

The simple combination of integer forecasting, consumption and daily re-planning simplifies the solution to deliver results. And, once explained to planners, makes sense to them and is easy to understand and manage. Much like Fischer’s moves, the ideas and concepts are deceptively simple and profound.

Consider also the simple and profound concept within Flowcasting of daily, net change re-planning. At our most recent implementation the solution works like this: for any product that had a sale or change that occurred yesterday, then the entire supply chain is re-forecast and re-planned from consumer to factory for that item.

In retail, on a daily basis, only about 5-15% of the products experience a change daily. Only these are re-planned daily, adjusting the future flows of inventory to ensure you remain in-stock and your inventory is productive. All projections are easily and simply converted into the language of the business so that the entire organization is working to a single set of numbers. One other benefit of net change, daily re-planning is that it also dramatically reduces system processing requirements.

Flowcasting is an easy concept and solution to understand and most people wholeheartedly agree with the premise. The trick to making it successful is to understand the nuances, embrace its simplicity and instill, over time, that kind of thinking in your planning organization.

Once you do, then, from experience, your supply chain and indeed your company will work like a Symphony of Placid Beauty!

 

Telephone Poles

telephone poles

It’s no secret that the Navy Seals are one of the most elite teams on the planet. Highly skilled, trained and motivated, they operate with exceptional levels of commitment and teamwork, performing missions around the world that demand excellence and pinpoint precision – like the missions to kill Bin Laden, or rescue Captain Phillips.

If you visit their training facilities in either Coronado or Virginia Beach you’re likely to notice one of their secrets to consistently churning out elite teams.

You’ll notice a stack of telephone poles.

They look like remains from a construction project or a stockpile for a utility, but for Seal Commanders they are sacred. They form the basis of a training routine called Log PT – an approach that instills teamwork, discipline, vulnerability and commitment.

Log PT is not complicated. Essentially six trainees perform a collection of maneuvers that look more like a barn raising. They lift them. Roll them. Carry them and move them from shoulder to shoulder. Do sit-ups while cradling them. Stand for long periods holding them above their heads.

There is no defined strategy for a team of trainees to follow. They must learn to work together, to build commitment and teamwork.

When done poorly, the poles buck and roll, and the team fights with each other, boiling emotions. However, when done well, it looks smooth, quiet and efficient. It has nothing to do with strength – rather it’s performed well when teamwork and harmony emerge. When a team member falters, almost invisibly another team member adjusts their efforts to keep the poles level and steady.

Log PT is the brainchild of Draper Kauffman, a WWII Veteran who got the idea for Log PT (and others that help form the core of Seal training) from being stationed with and serving with the Corps Franc, on the front lines in Germany.

Log PT was designed and first implemented in the late 1940s. And still, to this day, is used to train and prepare elite teams.

Think about that for a moment. With all the new and exciting technologies available today, a simple program based on teams working together and in harmony moving telephone poles around is the core technology used to produce elite teams and performance.

Let that sink in and the lesson on offer.

Everyday, if you’re like me, you’re being bombarded with claims of incredible breakthroughs of potential future performance with new and brilliant technologies – like AI, Big Data, Augmented Reality, Virtual Reality, Internet of Things, just to name a few. And to be fair, I believe the potential is and will be enormous.

The lesson here is that the most elite producing teams on the planet has yet to see the need or benefit of changing their approach – an approach that literally hasn’t changed since the 1940s.

Here’s an example from one of our clients that is consistent with the lesson.

When we demonstrate the Flowcasting planning process for one of our retail clients, many people are shocked to understand how the promotional sales forecast is derived.

It’s basically built from a demand planner looking at POS sales history for that item from past promotions and then, if needed, collaborating with the Category Leader – for situations where there is limited or no history and/or the promotional offer is significantly different than past offers.

They agree on what they think they will sell for the event and the system spreads that forecast down to the participating stores based on simple rules about that items contribution to sales, store by store.

That’s it. Pure simplicity.

Yet, like Log PT, it is delivering awesome results – better than any approaches used before. Helping to deliver industry leading in-stock for promotional events – a thorn for most retailers.

Planners and Category Leaders understand they need to work together, and they do, building commitment and accountability for the promotional sales forecast.

Please don’t think that I’m shitting on new technologies like AI, IoT and any others. I’m not. I believe that there is and will be enormous potential for these technologies and that they will also largely deliver on these promises.

But, I also believe in what is simple and works.

So do my client’s customers.

Ungrain

In 1983 Benjamin Libet, researcher in the Department of Physiology at the University of California, performed one of the most famous and controversial experiments in the history of neuroscience.

In simple terms, Libet’s experiment measured and timed the response of the neural circuitry of the brain, based on some very basic commands – like moving your left wrist, followed by your right wrist.  What he discovered is that there is a time lapse between the decisions our neural circuitry makes for us and our awareness of the situation.

What that means, in a nutshell, is that for basic operations and requests the brain has already been hardwired, or ingrained, into a conditioned response, basically without thought.  The brain has seen this movie (or ask) so many times that the response is automatic.

For us folks who are working on changing people’s behaviors and habits, we can relate.  People become ingrained in current practices, processes and ways of thinking and it usually takes considerable time and effort to change – the thinking and the response.

Libet, however, didn’t stop there.  Further work, research and experiments concluded that there were generally only two ways to change the history of the brain as it relates to a specific ask or task.  They are asking WHY and making a JOKE of the situation.

Let’s look at an important supply chain planning example and focus on the WHY.

To date, most retail planners, consultants and solution providers have firmly cemented and ingrained the thinking that to systemically create a forward looking time-phased forecast by item/store (or webstore) requires that you forecast at multiple levels and then spread the higher level forecasts down to the lower (store) level.

Initially the thinking was that the aggregate level forecast would be more accurate, and that is usually the case.  But some people realized that the higher level forecast was of no value – it’s the lowest level of forecast that drives the integrated supply chain.

Asking and wondering WHY enough times eventually surfaced that the higher level forecast was really only helpful in determining a selling pattern, especially for slower selling products where a pattern was difficult to detect.

Our colleague, Darryl, not only understood but asked WHY it was necessary to forecast at a higher level.  Couldn’t the pattern be determined, at the selling location, without the need and complexity of forecasting at a higher level.

Eventually, he arrived at a simple, sensible solution.  In a previous newsletter, I outlined the key elements of the approach but the key elements of the approach are:

  • An annual forecast is calculated, along with a decimal forecast (by day and week) for the 52 weeks that comprise the annual forecast
  • A category or department level selling pattern is calculated at the store location (or other’s if needed)
  • Simple user forecast thresholds are applied against the annual forecast to determine the forecast time period and how to determine the selling pattern – including using the category/department level pattern from above for slow sellers (to get the sales pattern)
  • The same thresholds determine whether to convert the decimal forecast to integers
  • For the forecasts that will be converted to integers, a random number between 0 and 1 is calculated, then the small decimal forecasts are added from there and once the cumulative forecast hits 1, then an integer forecast is 1 is used in that period, and the counter and randomizer starts again…this logic is applied to the 52 week forward looking forecast

Now, while the above is tougher to write to help understand, our experience in outlining this to people is that they not only understand, but it makes intuitive sense to them.

This solution was originally key functionality of the RedPrairie Collaborative Flowcasting solution and is now available within the JDA solution set, aptly named JDA Slow Mover Forecasting and Replenishment.

Yes, but does it work?

The graph below outlines the sales forecasts of our recent implementation of Flowcasting at a Canadian hardgoods retailer, using this exact approach:

Slow-sellers2

As you can see, a significant number of products are slow or very slow sellers (54% sell less than one unit per month at a store).  However, using this approach the company was able to improve in-stock by 6%, while also reducing and improving inventory performance.

Having an integer-like forecast for all these item/store combinations is important since it allows them to calculate time-phased DC and vendor replenishment plans, along with complete capacity and financial projections – allowing them to work to a single set of numbers.

In addition, the solution is so much simpler in terms of understanding, flexibility and processing requirements.

Given the above, people should embrace this solution full tilt.  This should be a no-brainer, right?

Nope, wrong.

Our old villain, ingrained, has helped cement the view of higher level forecasting in retail.

It’s ironic, and a little sad, that a number of people and companies who advise and help companies change and learn new and presumably better ways have not embraced this approach, and instead are still pushing old, tired and ineffective solutions.

They need to ungrain their thinking (ungrain is the opposite of ingrain and yes, I made this word up!).

My advice is simple: if you’re a retailer who is forecasting at a higher level, or you’re someone who’s pushing this approach, please stop.

Learn. Understand. See it yourself.  Ask WHY.  And, importantly…

Ungrain the old and begin to ingrain the new.

Princess Auto’s Flowcasting journey featured in Canadian Retailer magazine

CR_SC2017

Our client Princess Auto Ltd. is the subject of a feature article in the inaugural Supply Chain issue of Canadian Retailer magazine (published by the Retail Council of Canada). Click here to learn about how they are using the Flowcasting planning process to significantly improve in-stocks and profits while unleashing a new omnichannel fulfilment model. You can also download a PDF copy here.

 

Virtual Reality for the Retail Supply Chain

SimulatorFA18

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.