Your Sales Plan is NOT a Forecast!

Man is the only animal that laughs and weeps, for he is the only animal that is struck with the difference between what things are and what they ought to be. – William Hazlitt (1778-1830)

A Ferrari has a steering wheel. A fire truck also has a steering wheel.

A Ferrari has a clutch, brake and accelerator. A fire truck also has a clutch, brake and accelerator.

Most Ferraris are red. Most fire trucks are also red.

A new Ferrari costs several hundred thousand dollars. A new fire truck also costs several hundred thousand dollars.

Ergo, Ferrari = Fire Truck.

That was an absurd leap to make, I know, but no more absurd than using the terms “sales plan” and “sales forecast” interchangeably in a retail setting. Yes, they are each intended to represent a consensus view of future sales, but that’s pretty much where the similarity ends. They differ significantly with regard to purpose, level of detail and frequency of update.

Purpose

The purpose of the sales plan is to set future goals for the business that are grounded in strategy and (hopefully) realism. Its job is to quantify and articulate the “Why” and with a bit of a light touch on the “What” and the “How”. It’s about predicting what we’re trying to make happen.

The purpose of the operational sales forecast is to subjectively predict future customer behaviour based on observed customer demand to date, augmented with information about known upcoming occurrences – such as near term weather events, planned promotions and assortment changes – that may make customers behave differently. It’s all about the “What” and the “How” and its purpose is to foresee what we think is going to happen based on all available information at any one time.

Level of Detail

The sales plan is an aggregate weekly or monthly view of expected sales for a category of goods in dollars. Factored into the plan are category strategies and assumptions (“we’ll promote this category very heavily in the back half” or “we will expand the assortment by 20% to become more dominant”), but usually lacking in the specific details which will be worked out as the year unfolds.

The operational sales forecast is a detailed projection by item/location/week in units, which is how customers actually demand product. It incorporates all of the specific details that flow out of the sales plan whenever they become available.

Frequency of Update

The sales plan is generally drafted once toward the end of a fiscal year so as to get approval for the strategies that will be employed to drive toward the plan for the upcoming year.

The operational sales forecast is updated and rolled forward at least weekly so as to drive the supply chain to respond to what’s expected to happen based on everything that has happened to date up to and including yesterday.

“Reconciling” the Plan and the Forecast

Being more elemental, the operational forecast can be easily converted to dollars and rolled up to the same level at which the sales plan was drafted for easy comparison.

Whenever this is done, it’s not uncommon to see that the rolled up operational forecast does not match the sales plan for any future time period. Nor should it. And based on the differences between them discussed above, how could it?

This should not be panic inducing, rather a call to action:

“According to the sales plan that was drafted months ago, Category X should be booking $10 million in sales over the next 13 weeks.”

“According to the sales forecast that was most recently updated yesterday to include all of the details that are driving customer behaviour for the items in Category X, that ain’t gonna happen.”

Valuable information to have, is it not? Especially since the next 13 weeks are still out there in a future that has yet to transpire.

Clearly assumptions were made when the sales plan was drafted that are not coming to pass. Which assumptions were they and what can we do about them?

While a retailer can’t directly control customer behaviour (wouldn’t that be grand?), they have many weapons in their arsenal to influence it significantly: advertising, pricing, promotions, assortment, cross-selling – the list goes on.

The predicted gap between the plan and the forecast drives tactical action to close the gap:

Maybe it turns out that the tactics you employ will not close the gap completely. Maybe you’re okay with it because the category is expected to track ahead later in the year. Maybe another category will pick up the slack, making the overall plan whole. Or maybe you still don’t like what you’re seeing and need to sharpen your pencil again on your assumptions and tactics.

Good thing your sales plan is separate and distinct from your sales forecast so that you can know about those gaps in advance and actually do something about them.

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.

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.