I’m From Missouri

 

“I am from a state that raises corn and cotton and cockleburs and Democrats, and frothy eloquence neither convinces nor satisfies me. I am from Missouri. You have got to show me.” – William Duncan Vandiver, US Congressman, speech at 1899 naval banquet

missouri

“How are you going to incorporate Big Data into your supply chain planning processes?”

It’s a question we hear often (mostly from fellow consultants).

Our typical response is: “I’m not sure. What are you talking about?”

Them: “You know, accessing social media and weather data to detect demand trends and then incorporating the results into your sales forecasting process.”

Us: “Wow, that sounds pretty awesome. Can you put me in touch with a retailer who has actually done this successfully and is achieving benefit from it?”

Them: <crickets>

I’m not trying to be cheeky here. On the face of it, this seems to make some sense. We know that changes in the weather can affect demand for certain items. But sales happen on specific items at specific stores.

It seems to me that for weather data to be of value, we must be able to accurately predict temperature and precipitation far enough out into the future to be able to respond. Not only that, but these accurate predictions need to also be very geographically specific – markets 10 miles from each other can experience very different weather on different days.

Seems a bit of a stretch, but let’s suppose that’s possible. Now, you need to be able to quantify the impact those weather predictions will have on each specific item sold in each specific store in order for the upstream supply chain to respond.

Is that even possible? Maybe. But I’ve never seen it, nor have I even seen a plausible explanation as to how it could be achieved.

With regard to social media and browsing data, I have to say that I’m even more skeptical. I get that clicks that result in purchases are clear signals of demand, but if a discussion about a product is trending on Twitter or getting a high number of page views on your e-commerce site (without a corresponding purchase), how exactly do you update your forecasts for specific items in specific locations once you have visibility to this information?

If you were somehow able to track how many customers in a brick and mortar store pick up a product, read the label, then place it back on the shelf, would that change your future sales expectation?

Clearly there’s a lot about Big Data that I don’t know.

But here’s something I do know. A retailer who recently implemented Flowcasting is currently achieving sustained daily in-stock levels between 97% and 98% (it was at 91% previously – right around the industry average). This is an ‘all in’ number, meaning that it encompasses all actively replenished products across all stores, including seasonal items and items on promotion.

With some continuous improvement efforts and maybe some operational changes, I have no doubt that they can get to be sustainably above 98% in stock. They are not currently using any weather or social media Big Data.

This I have seen.

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!

Cross Purposes

 

A compromise is the art of dividing a cake in such a way that everyone believes he has the biggest piece. – Ludwig Erhard (1897 – 1977)

 

Last week, I had the chance to catch up with a good friend and colleague of many years. His name is Ian and he is the VP of Supply Chain at a mid-sized retailer (with vast prior experience at a large retailer).

After a couple of beers, he asked me point blank: “Forecasting and Replenishment. One job or two?”

Without hesitation, I responded “Two!” Then I proceeded to describe the differences in skill sets, business relationships and aptitudes between a Demand Planner and a Supply Planner.

“Okay”, he said. “Who does the Demand Planning group report to?”

That’s a very interesting question indeed.

The goal of the demand planning process is to create a sales forecast that is as accurate and unbiased as possible. In retail, the process of coming up with a forecast is typically a “joint effort” between the Category Manager and the Supply Chain Planner.

The Category Manager is measured primarily on sales. Therefore he/she has a tendency to make optimistic projections and bias the forecast upward, knowing that a higher forecast will buy more inventory, thereby (theoretically) reducing the likelihood of lost sales.

The Supply Chain Planner is measured primarily on inventory turns. Therefore he/she has a tendency to “keep the forecast lean” to avoid carryover inventory after a promotion or selling season.

Therein lies the rub. If you give control of the forecasting process to the Merchandising group, Supply Chain feels like you’re “putting the fox in charge of the henhouse”. If the forecasting process falls under Supply Chain, Merchandising feels like they have no control over one of the key inputs that drive their businesses.

So should the Demand Planning function reside within Merchandising or Supply Chain?

Neither.

Think about it. Neither group can be faulted for exhibiting behaviour on which they are rewarded. The problem is that they have competing objectives and the biases on either side can have a direct negative impact on the P&L.

That’s why the Demand Planning function needs to report to someone who has accountability for the entire P&L – either the CEO or, more practically, the CFO.

Remember the goal for the sales forecast: As accurate and as unbiased as possible. By having Demand Planners report into Finance, they can be effective mediators between the competing groups and would have “a seat at the table” when matters relating to the sales forecast are discussed (promotions, product launches, safety stock policies, etc.)

Their job would be to chair S&OP meetings with their Merchandising and Supply Chain counterparts and hear both sides of the story with an objective ear. Without either group having the direct ability to impose their biases on the forecast, they must instead make a convincing case to the Demand Planner to support their view.

As a consequence, the current “blurred lines” of accountability are made clear once and for all:

Merchandising: Stimulate demand and be accountable for sales and gross margin.

Demand Planning: Forecast demand and be accountable for forecast quality.

Supply Chain: Optimize supply and be accountable for inventory turns and availability.

Mentally Separating Demand and Supply

In order for the replenishment planning process to be as flexible as possible going into the future, it is imperative that a clear distinction be made between demand planning and supply planning.

The goal of the demand planning process is to predict behaviour of customers. Customer demand cannot be directly controlled and must be taken as given in the supply chain. We do our best to predict this behaviour and schedule resources (i.e. supply) as efficiently as possible to support the wants of customers. When we have our demand planning hats on, the furthest thing from our minds should be considering how this demand will be satisfied. Demand is demand, and it is not subject to constraints. This is what keeps the demand planning process as pure as possible.

Once you have a handle on your demand, proper supply decisions can be made to ensure that demand is satisfied. That’s the mental separation — demand is not within our scope of control and must be taken as given, while supply decisions can be made and remade in order to best satisfy changing demand patterns.