Compliments from a CEO

It’s always nice and also encouraging to hear positive comments from a retail CEO about Flowcasting and supply chain management in general. Below are some nice compliments from Ken Larson, President & CEO of Princess Auto Ltd, about Flowcasting, supply chain and the team (both internal and external) that helped make it happen. Thanks for the kind words Ken!

Working backwards

You’d likely agree that Amazon is a very innovative company.  AWS, Prime, Kindle, One-click-shopping are examples of innovations they’ve delivered through a process called Working Backwards.  Working Backwards is a systemic way to surface and vet ideas that sometimes lead to new products or services.  The key tenant of the approach is to begin by defining the product’s (or service) arrival, and then work backwards from that point until the teams achieve clarity of thought around what they will deliver.  

The main tool used to accomplish this clarity of thought is the PR/FAQ document – short for Press Release / Frequently Asked Questions.  The document is written from the perspective of the customer and is dated into the future, when they believe the innovation will arrive in the marketplace.  What’s simple, yet brilliant, about this approach is that it keeps teams focused on delivering something significant, valuable and meaningful to customers – rather than many approaches that are essentially based on the idea of incrementing-your-way-to-greatness.

You may not know, but Flowcasting is also based on the concept of Working Backwards.

Loyal disciples understand that the Flowcasting process starts with a forecast of consumer demand, by product and selling location (e.g., store, etc.).  Conceptually, what’s a forecast of consumer demand?  It’s when and where the customer wants to acquire the product – i.e., when and where it needs to arrive in their hands.

Flowcasting integrates the supply chain from this forecast of consumer demand by working backwards using an approach called arrival based planning.  For any product at any location, arrival based planning calculates planned shipments of when and how much inventory needs to arrive – scheduling a shipment so that the arrival date and quantity ensures the projected inventory doesn’t drop below safety stock.  

The basic logic is simple:

For each item/location:
1. Figure out what you expect to sell (or calculate what you’ll ship) 
2. Figure out what you have and what your constraints are
3. Figure out when you will need more product to arrive
4. Use the arrival based plan to figure out when you need to ship

The concept of planned shipments and arrival based planning is foreign to most retail demand and supply planners. After we do an educational session with planners, we often break people into teams and ask them to calculate a shipment based plan, using arrival based logic, with an example something like this:

Without exception, every retail client we’ve worked with struggles with this simple ask. Everyone has been so conditioned to focus on “ordering” that they struggle to understand that ordering (or committing the planned shipment) is the last decision, not the first. They are focused on “do we need to order” in week 1, rather than planning arrivals and the corresponding ship dates (i.e., planned shipments) first. 

Planned shipments are the foundational construct of Flowcasting and how the process integrates the retail supply chain to ensure the fundamental principle is achieved – that is, a valid simulation of reality.  Every planned shipment consists of an arrival date (when the product will arrive at the destination) and a ship date (when the product will ship from the supplying location).

Flowcasting plans shipments over the entire planning horizon and shares these projections with suppliers and other stakeholders in order to help them plan and improve productivity.  For suppliers we often refer to what is shared with them as a supplier schedule – that is, the projection of planned quantities and their associated ship dates by product and origin/destination.  

Ship dates are the key element to anchor the supplier schedule on.  That’s because ship dates are very specific from a supply chain and work perspective.  It’s when the inventory needs to be available and also when transportation needs to be scheduled to initiate the delivery.

The supplier schedule is, in most cases, the culmination of Working Backwards for a retailer who is using Flowcasting.  From the forecast of consumer demand, we work backwards to calculate when product needs to arrive and ship, through the entire distribution network, right back to when the factory needs to ship the product – integrating the entire supply chain via a series of dependent, cascaded planned shipments.

When you first hear the phrase Working Backwards it sounds like a dumb idea and implies you’re heading in the wrong direction.  Turns out, it’s been a proven and brilliant way to drive innovation.  

It also turns out to be the best way to plan inventory flows for the retail supply chain.

The Arrival Based Plan
For those students, here is the arrival based plan for the example outlined above:

What’s important to understand is that the planned arrivals that are calculated above would be the same, regardless of supply source.  They indicate the quantity and timing of a shipments arrival and are not dependent on the supply source.  The planned shipment, of course, is dependent on the supplying source and the transit lead time.

This make arrival based planning a powerful approach since it enables you to easily plan a change of source well into the future and have all the cascaded dependent demand reflect a valid simulation of reality.

Sides of a Coin

Most controversies would soon be ended, if those engaged in them would first accurately define their terms, and then adhere to their definitions. – Tryon Edwards

simple: easy to understand, deal with, use, etc.

simplistic: characterized by extreme simplism; oversimplified

complex: composed of many interconnected parts; compound; composite

complicated: difficult to analyze, understand, explain, etc.

Such small distinctions.

Such calamity when those distinctions are not properly acknowledged, particularly when applied to the retail supply chain.

Let’s start here:

  • Problems that are complex can usually broken down into smaller problems, each of which can be simple
  • Problems that are complicated are often intractable – they can’t easily be broken into chunks and require some sort of breakthrough to be solved (think peace in the Middle East)
  • Problems that are simple – well, they’re not really problems at all, are they?

Now here’s where – in my experience at least – retailers start running into trouble.

Problem #1: Seeing complexity as complication

If you’ve ever read articles about the challenges of planning the retail supply chain, you’ve probably seen a diagram or two that looks something like this (if not worse):

The implication is clear: The retail supply chain is a vast, sophisticated web of relationships between and among various entities. Not only that, but the problem becomes more mind boggling the closer you get to the customer, as depicted below:

I mean, look at all those arrows!

To be sure, the retail supply chain planning problem is large in terms of the number of items, locations and source/destination relationships. The combinations can get into the tens – if not hundreds – of millions.

But is it truly an enormous and complicated problem or merely an enormous number of simple problems?

In contradiction to the popular proverb, sometimes it’s necessary to focus on the trees, not the forest.

How you consider the problem will in large part determine your level of success at solving it. Complication is often a self inflicted wound (more on that later).

Problem #2: Seeing simplistic as simple

Just as overcomplication leads to trouble, so does oversimplification.

Best summed up by Albert Einstein:

People love this quote because they feel it very neatly sums up Occam’s Razor. Then they further reduce it to a design philosophy like “the simpler, the better”.

But the real power in that quote doesn’t reside in the first part (“Everything should be made as simple as possible.”), rather in the second: But not simpler.

In a retail planning construct, I’ve most often seen this line crossed when the topic is forecasting for slow selling item/stores. Demand forecasting as a discipline originated in manufacturing where volumes are high and SKU counts are low. As a consequence, most mature forecasting methods are designed to predict time series with continuous demand.

When you look at retail consumer demand at item/store level, a significant portion of those demand streams (often more than 70% for hardlines and specialty retailers) sell fewer than one unit per week.

So we have intermittent demand streams and tools that only really work well with continuous demand streams. So what’s the solution?

One of the most common responses to that question is: “Screw it. It’s not even worth forecasting those items. Just set a minimum and maximum stock value for ordering and move on.”

That position is certainly not difficult to understand, but is this really keeping it simple or being overly simplistic?

Here are some follow-up questions:

  • What if a particular item is fast selling at some locations and slow selling at others? Would you forecast it at some locations but not at others? How would a demand planner manage that?
  • If not every item in every location is being forecasted, then how do plan future replenishment volumes? Not just at the stores, but at DCs as well?
  • If not every item is forecasted, then it’s not possible to do rollups for reporting and analysis, so how do you fill in the gaps?

Because a simplistic solution was proposed that only addresses part of a complex problem, we have created a problem that is complicated.

This is akin to looking at a single tree without even recognizing that there are other trees nearby, let alone seeing a forest.

Things are only as complicated as you choose to make them, but they also may not be as simple as they seem.

Trust the process

Nick Saban is a brilliant college football coach and widely heralded as a football genius. At time of writing, his coaching record stands at 261 wins, 65 losses and 1 tie. He’s won 17 Bowl games along with 7 national titles (the most ever) and counting.

If you’re a fan of the Alabama Crimson Tide, in a state where college football is king, Saban is arguably more popular than Jesus. Fanatics think he is Jesus.

When asked about his unrivaled success, Saban offers a counter-intuitive philosophy that’s guided his coaching career, anchored on two fundamental principles:

  1. Don’t focus on the outcome
  2. Trust the process

Incredibly, Saban doesn’t focus on the result – which, for college football – like most sports – is whether you win or lose. Sure, make no mistake about it, Saban wants to win, it’s just he believes that the path to long term success is by trusting the coaching process.

His belief is that by coaching his team, repeatedly and without fail, so that they can execute their designed plays on offense and coaching schemes on defense, he’ll maximize his odds of winning. Losses are important to this process as it provides the team the opportunity to review the film and see where the process failed – either in execution or, sometimes, in coaching and design. Which leads to more coaching, practice and trust in the process.

Trusting the process is a philosophy that has served Saban and the Crimson Tide incredibly well.

We can learn a lot from Nick’s nuggets of wisdom.

Given that we’re often referred to as the Salty Old Sea Dogs of Flowcasting, it’s fair to say that we’ve been around the block a few times and, over time, changed our thinking often. No more than so than in developing, managing and measuring the retail forecasting/demand planning process.

For most retailers, the number of item/store products that sell less than 26 units a year (about 1 every two weeks) can be pretty significant – often comprising 30-50% of a retailer’s assortment. You wouldn’t expect to be as accurate in determining a forecast for these types of products, since there is a fairly large element of probability involved – as an example, based on history, you can feel confident that 1 unit sells every month but you’re not sure when it will be.

While it’s tempting to aggregate the lower level item/store forecasts up to a higher level and assess forecast performance, that’s of little use to anyone – after all, customers buy products in stores, or online, to be acquired or delivered at their preferred location. They don’t buy them at some aggregate level. Not to mention that item/store replenishment plans are driven from these forecasts and the dependent demand is cascaded throughout the supply network.

Like Saban, we work with our clients to help them understand and hopefully instill the idea of assessing the forecasting process by determining something called forecast reasonableness.

So then, what’s a reasonable forecast?

The following diagram outlines, conceptually, what we’re talking about:

The idea is to assess the reasonableness of the forecasts based on a sliding scale determined by selling rate. As an example, you wouldn’t expect to have as accurate a forecast for a product that sold 12 units a year as you would for something that sold 1200 units a year. Of course, you need to determine what’s a reasonable tolerance and sliding scale but from experience that’s not too difficult.

If the item/store forecast is within tolerance then the process/solution is producing a reasonable forecast. The beautiful thing is that the planner spends no time chasing these forecasts since, in all likelihood very little can be done to improve the process/outcome for these.

In practice, forecast reasonableness is an exception condition for the demand planners to action. For the item/store forecasts that are outside of tolerance, the planner can investigate these, see if the same item is outside of tolerance for a number of stores and determine if anything is systemically happening or could be improved in the process to bring them within tolerance.

To determine how well the forecasting process is working is simple. What percentage of the item/store forecasts is within tolerance?

We believe that, in retail, forecast reasonableness should replace traditional measures of forecast accuracy (like MAPE, WMAPE, etc., that were developed for more continuous demand streams in manufacturing and distribution).

Now before you think we’re completely mental, here’s something to ponder on. One of our retail clients, who plan using the Flowcasting process, does not measure baseline forecast accuracy.

Instead, they use a forecast reasonableness exception to evaluate the process, honing in on any forecasts that are not within tolerance to see if there is anything that can explain this and, potentially, how they might “improve the process”.
During the time they’ve not measured forecast accuracy they improved daily in-stock from an average of 91.7% to an average of 97.7%, while also improving inventory performance.

For a customer, in-stock is everything. They couldn’t care less about forecast accuracy.

Maybe you shouldn’t either.

Store Inventory Accuracy and Deming’s 14 Points

Our system of make-and-inspect, which if applied to making toast would be expressed: “You burn, I’ll scrape.” – W. Edwards Deming (1900-1993)

What would Dr. Deming make of retail store inventory accuracy?

Impossible to know for a couple of reasons. First, he died nearly thirty years ago. Second, the bulk of his career was devoted to the attainment of total quality management in manufacturing. That said, the spirit of his famous 14 Points for Management first published in his 1982 book Out of the Crisis applies to – well, pretty much every facet of every business and store inventory accuracy is no exception.

Point 1: Create constancy of purpose toward improvement of product and service, with the aim to become competitive and to stay in business, and to provide jobs.

“Defects are not free. Somebody makes them, and gets paid for making them.”


If there’s one thing that the COVID-19 pandemic has taught retailers, it’s that when your system on hand records don’t match the physical stock in the store, it’s a real problem for customer service and productivity. When your sales primarily come from walk-in business, there’s really no reliable way of knowing how many customers walked out unsatisfied or made a substitution as a result of an empty shelf.

When you assign online pickup orders to be picked at a store because the system on hand balance shows stock, the curtain is unceremoniously ripped away. How many orders couldn’t be fulfilled because the available stock in the system couldn’t be found in the store? How much wasted time was spent fruitlessly trying to find the stock to pick the orders? 

Retailers don’t measure their inventory accuracy. They must.

Retailers don’t adequately research the process and transactional errors that cause their inventory to become inaccurate in the first place. They must. 

Before any of that can happen, management needs to actually care about inventory accuracy.

Point 2: Adopt the new philosophy. We are in a new economic age. Western management must awaken to the challenge, must learn their responsibilities, and take on leadership for change.

“To manage one must lead. To lead, one must understand the work that he and his people are responsible for.”

Inaccurate stock records don’t “just happen”. They are the result of one of two things:

  1. People aren’t following the correct processes for managing stock
  2. People are correctly following flawed processes for managing stock

In either case, the responsibility falls on management to correct these issues. This can’t be accomplished without diving deep to understand the processes and behaviours that are causing errors.

Point 3: Cease dependence on inspection to achieve quality. Eliminate the need for inspection on a mass basis by building quality into the product in the first place.

“Inspection does not improve the quality, nor guarantee quality. Inspection is too late. The quality, good or bad, is already in the product.”

This is one that retailers generally don’t understand. At all. Most “inventory accuracy” programs focus on trying to optimize counting frequency. Items with historically poor inventory accuracy are cycle counted and corrected more frequently than items with fewer historical errors, with little investigation as to why those errors are happening in the first place. This approach is really “problem solving theatre” – there are process issues that are causing the errors and constantly repairing the output without addressing the root causes of why the records became inaccurate in the first place will never lead to sustained inventory accuracy.

Point 4: End the practice of awarding business on the basis of price tag. Instead, minimize total cost. Move toward a single supplier for any one item, on a long-term relationship of loyalty and trust.

“The result of long-term relationships is better and better quality, and lower and lower costs.”

Are you buying products from suppliers that make it more difficult to keep stock accurate in stores? Do they wrap several different items in nearly identical packaging to save money at the expense of confusing store staff and customers? Are the barcodes applied with easily removeable (and switchable) stickers? Are the barcodes easy to find and scan at the checkout?

This is often small potatoes when compared to the in store process and behavioural issues, but every little bit helps. Missed sales caused by inaccurate stock affects the supplier too, so to the extent that they can work with retailers to avoid being part of the problem, everyone will benefit.

Point 5: Improve constantly and forever the system of production and service, to improve quality and productivity, and thus constantly decrease costs.

“Putting out fires is not improvement of the process. Neither is discovery and removal of a special cause detected by a point out of control. This only puts the process back to where it should have been in the first place.”

Focusing on inaccurate stock records is trying to manage the output. Inaccurate inventory is caused by processes that result in inaccurate transactions which in turn result in inaccurate on hand balances.

If you research a variance and determine it was because Mary made a mistake at the checkout, what you’ve found is an explanation for that particular error, not a root cause.

Why did Mary make that mistake? Was it a specific one-off event that won’t likely ever be repeated? Has she been properly trained on proper checkout procedures? Are the checkout procedures themselves flawed? Has management instructed Mary to focus on speed over accuracy? Are other cashiers making similar mistakes for the same reasons?

Point 6: Institute training on the job.

“People don’t like to make mistakes.”

The retail industry in general is notorious for high turnover in front line staff – you know, the people who actually transact stock movements within the store. As a result, it can be tempting to skimp on training new people for fear that your investment won’t be returned. When new people have questions, they need to go to a manager for instruction on what to do. More often than not, busy managers will provide shortcut solutions that are designed to get the problem off their plates as quickly as possible.

Is saving money on training actually saving money?

Point 7: Institute leadership. The aim of supervision should be to help people and machines and gadgets to do a better job. Supervision of management is in need of overhaul, as well as supervision of production workers.

“It is not enough to do your best; you must know what to do, and then do your best.”

Training is a good start, but it’s not enough to sustain inventory accuracy. Do people understand why inventory accuracy is important to customers and fellow team members and how their role can impact it?

Point 8: Drive out fear, so that everyone may work effectively for the company.

“Where there is fear, you do not get honest figures.”

Poor inventory accuracy should not be seen as a reflection of people’s performance, rather the performance of the process. If inventory discrepancies discovered in cycle counts result in witch hunts that are used to find culprits and lay blame, people will quickly learn “the right amount” of error they can report to avoid suspicion on the low end and recriminations on the high end. The true problems will remain buried under rosy reports that everyone can reference to argue that a problem doesn’t exist.

Point 9: Break down barriers between departments. People in research, design, sales, and production must work as a team, to foresee problems of production and in use that may be encountered with the product or service.

“Quality is everyone’s responsibility.”

Contributors to inaccurate inventory records can be found anywhere and processes (both internal and external to the store) can be the cause. Is an inventory accuracy lens being used when designing new processes and procedures in Loss Prevention, Merchandising, Sourcing, DC Picking, Store Receiving and Stock Management?

Point 10: Eliminate slogans, exhortations, and targets for the work force asking for zero defects and new levels of productivity. Such exhortations only create adversarial relationships, as the bulk of the causes of low quality and low productivity belong to the system and thus lie beyond the power of the work force.

“Hopes without a method to achieve them will remain mere hopes.”

There may well be some store employees who are deliberately trying to sabotage the business, but they are in a very small minority. Telling people “We need you to keep your stock more accurate” without first investing in education, training and the proper tools is like giving them a mule and telling them to go out and win the Kentucky Derby. 

Point 11: 11a. Eliminate work standards (quotas) on the factory floor. Substitute leadership. 11b. Eliminate management by objective. Eliminate management by numbers, numerical goals. Substitute leadership.

“Every system is perfectly designed to get the results it gets.”

Don’t let this one fool you. Deming was all about data collection and measurement of results. It’s what you do with the data that counts. Stock variance reports can alert management to where the problems may lie, but the only path to a solution is to dig in and understand the process in detail. Once a process change is made that you feel should have solved the problem, future rounds of data collection will tell you whether or not you were successful. If you weren’t successful, you need to dig in again, because there is something you missed.

Point 12: 12a. Remove barriers that rob the hourly worker of his right to pride of workmanship. The responsibility of supervisors must be changed from sheer numbers to quality. 12b. Remove barriers that rob people in management and in engineering of their right to pride of workmanship. This means, inter alia, abolishment of the annual or merit rating and of management by objective.

“When one understands who depends on me, then I may take joy in my work.”

See Points 6 and 7 above. The impact to customers and fellow team members of doing things that cause stock to become inaccurate is easy to explain. People want to do a good job, but they need to be given the right education, training and tools.

13. Institute a vigorous program of education and self-improvement.

“Learning is not complusary. Neither is survival.”

When it comes to store inventory accuracy, there’s never a point at which you are finished. There will always be new causes of errors and processes that need improving.

14. Put everybody in the company to work to accomplish the transformation. The transformation is everybody’s job.

“Long-term commitment to new learning and new philosophy is required of any management that seeks transformation. The timid and the fainthearted, and people that expect quick results, are doomed to disappointment.”

Store perpetual inventory has been around for decades. So have the process gaps, bad habits and lack of care that makes inventory records inaccurate. There are a lot of people involved and a lot of moving parts that will make it difficult to attain and sustain high levels of inventory accuracy at stores. It will take effort. It will cost some money. It won’t be easy.

But living with the impacts of poor on hand accuracy is no walk in the park either. It’s taking MORE effort, costing MORE money and making things MORE difficult on a daily basis. 

Wrong becomes right

Phil Tetlock spent almost two decades determining people’s ability to forecast specific events – things like elections and the outcomes of potential geopolitical decisions. Unfortunately, the results were not impressive. Most people were about as accurate as a well-fed, dart-throwing chimpanzee.

There were a small number of notable exceptions. A small group of people consistently provided quite accurate forecasts – people he aptly named “super-forecasters”.

In a subsequent forecasting tournament organized by the Intelligence Advanced Research Projects Activity (IARPA) – a focused branch of the United States intelligence community, the super-forecasters trounced teams of professors and “forecasting experts” by wide margins.

What made the super-forecasters so super?

It wasn’t intelligence or that they had more experience than others. In fact, in many cases, they were mostly amateurs yet they outperformed the CIA’s best and brightest (who also had the advantage of years of experience and classified information). Armed with only Google, the super-forecasters beat the CIA, on average, by 30%.

What made them great at being right was they were great at being wrong!

The difference in their ability to forecast was simple, yet crucial. The super-forecasters changed their minds – a lot.

Not a huge, 180-degree shift, but subtle revisions to their predictions as they learned new information. As an example, one of the consistently top super-forecasters would routinely change his mind at least a dozen times on a prediction and, sometimes, as often as forty or fifty times.

Importantly, most viewed a revised forecast based on new information not as changing an initially wrong forecast but rather as updating it. Turns out, updating is the secret to being a great, or super, forecaster.

The concept of updating is important in Flowcasting as well.

As loyal Flowcasters know, an important component of the process is the sharing of what we call a supplier schedule – that is, a projection, by item and delivery location of how many units are needed to ship over a long time horizon (typically 52+ weeks).

If the schedule indicates that, 39 weeks from now, the supplier will need to ship 10440 units of a product to a location, what’s the chance that this projection (i.e., forecast) is perfectly accurate? Pretty low, right? And it doesn’t need to be – it just needs to be reasonable.

A week later, and guess what? The supplier schedule has been re-calculated and updated to indicate that 10400 units are needed to ship in that particular week (perhaps even on a different day). The updated forecast is more right than the previous one. This process of minor revisions continues as the projections are updated until it’s actually time to ship (i.e., when the planned shipment has reached the agreed-upon order release horizon).

In retail, supplier scheduling is the super-forecaster for suppliers – recalibrating and subtly updating the forward looking projections, based on the latest information until…

Wrong becomes right.

Flipping your thinking

From toddler to teenager, most of us had a fairly similar educational experience: The teacher would stand at the front of the room and spew out information that the students were to absorb. Then they would assign homework that would, theoretically at least, test how well you absorbed the content. The homework assignments would then be scored by the teacher and – if you were lucky – you might find some scrawled notes in the margin to give you a clue as to where you may have gone astray.

All this assumes, of course, that you didn’t just copy your homework from a smart (if gullible) friend, thereby completely circumventing the ability of the homework assignment to test knowledge. Not to say that this approach was completely ineffective. Somehow, most of us did learn what we needed to know to become productive members of society. That said, when the best praise you can muster is that it’s “not completely ineffective”, then you are basically admitting that there is ample room for improvement. 

Karl Fish is a veteran teacher with 20 years of experience. He teaches high school math in a town just south of Denver, Colorado.  Karl thought he could do better for his students than “not completely ineffective”, so he decided to flip the traditional thinking on its head.

Instead of using class-time to “teach” in the traditional sense, Karl tapes his lessons and uploads them to YouTube. Classroom time is used for application and practice.  His students are required to watch the lecture whenever and wherever it is most convenient for them.  What would be traditionally considered “homework” is actually done during in-class time.

The result of this flip in thinking has been significantly improved understanding of the content. Working through examples and case studies not only improves the students understanding, but also improves their ability to collaborate with fellow students and Karl himself.

Contrast this approach with doing your homework in the evenings (maybe even the wee hours of the morning). If you get stuck, there are few alternatives other than to become increasingly frustrated and demoralized.

In Karl’s class, you can pose your question to a group (many of whom are likely struggling with the same question) and work together to solve the problem. What better skill and habits are there for someone to learn in high school?

Retail supply chain planning is also in need of a flip in thinking.

Traditional thinking in retail has ingrained into people’s heads that ordering is the key decision a supply chain planner needs to make. Day in and day out the retail supply chain planner only has 2 questions:

1) Should I order today?

2) How much should I order?

All anyone can talk about nowadays is “demand driven supply chains” that are super-responsive to consumer demand – yet the entire planning approach is geared toward figuring out when to place an order upstream with, at best, an indirect link to the actual customer demand.

Flowcasting flips that thinking completely. In a nutshell, the decision to place an order is a mere after-effect of the planning process (not the one and only decision) and, generally, it should be performed by a computer, not a human being.

Instead of asking “When and how much should I order”, maybe the first question should be “When does more stock need to arrive?” – Isn’t that what’s really important to your ability to stay in stock and serve a customer?

By focusing on this question first, new thinking emerges. Once you understand when product needs to arrive, then you can calculate when you need product to ship (based on where it’s coming from) and when you need to order.

Of course, to answer this question you’ll need a system to project inventory and product arrival dates well into the future.  And to calculate the corresponding ship dates and order dates. The basic change in philosophy is simple – to really know when product needs to be ordered, you must first know when it needs to arrive at the destination.

While this may sound quite simple and logical, in practice it requires a great deal of education and understanding to make such a flip – particularly if people have been “ordering” for a long time.

In our experience, most retailers continue to subscribe to the “order first, ask questions later” philosophy and flipping to an arrival based planning approach like Flowcasting will not be a slam dunk, regardless of how logical it sounds.

If you’re struggling with the concept, we’d be happy to schedule some homework time with you and your team.

Principles

Folks that know us well and have worked with us, know we’re what you might call principles freaks.  A decent chunk of time and effort we spend helping retailers implement Flowcasting is oriented to instilling a set of principles, which guide our thinking and, hopefully over time, our clients.

Julia Galef, in her brilliant book, The Scout Mindset, beautifully outlines the paradox of principles in a chapter aptly named, “How To Be Wrong”…

Many principles sound obvious and that you know them already.  But “knowing” a principle, in the sense that you read it and say, “Yes, I know that,” is different from having internalized it in a way that actually changes how you think.