Sales is what you buy. Demand is what you want. Growth comes from bringing the two together.

Interesting article as always of the Harvard Business Review. 

It reminds me of my customer decision making process, which I highly appreciated, and that gave me the love of customer relationship management. 

The article highlights two main ideas.

The difference between demand and sales

Of course, while working on category management plan or to forecast the outcomes of a new project, you need to set up some goals, backed up by data. Most of the time, you extrapolate data from sales figures. But as the article underline, sales data are slim to have the big picture. It does not take into account the impact  out of stocks, suboptimal assortment, pricing inefficiencies, difficult POS experiences, misaligned brands, and redundant innovation. The whole environment have an impact on sales.

Sales data provide you with figures that are difficult to take clearly due to all the factors that may alter one customer decision.

On the other hand demand data is also difficult to reach as we touch to the whole complexity of human emotions and complex decision making process. You need to have tools like brand mapping, that are difficult to transfert into figures. It is like working with your left and then your right brain. Easier said than done.

You need both information though to make the right answer. Same thing with the Direct Profit by Products analyze which can't be the single way to pick a product range, you need to understand all the strategical aspect of your demand, in order to make the right choice to suit your customers.

Working together with the different stakeholders

The second part of the article that I like is about integrating all marketing data. Indeed, there are three main actors that own a part of the information needed:

- Suppliers own customer data

- Retailers own shopper data

- Media own watchers data

It is the essence of category management: suppliers and retailers working together to leverage all these data in order to have the best respond to the demand. As the amount of data available is growing and becoming more precise, there is a lot of potential to unfold.

A New Article About Direct Profit by Product

Here is anew article I wanted to share with you about Direct Profit by Product. The Direct profit by product index is a method used in retailing to analyze the true profitability of one product, taken into account all the components of its margin and the cost related to its sale.

The article has been published in 1988, which proves that the idea of DPP has been there for quite a while, even though it is still not much used by retailers. This article shows the result of a study made in a supermarket chain on the mapple syrup categories. This is also the reason why the article is interesting, is that it gives a clear case study on how to use DPP.

Here are some of the highlights of the article.

There are 3 types of Direct Product Costs :

• Warehouse costs, 
• Transportation costs
• Store costs

The allocation of costs is a function of several factors:

•  Cubic volume of the unit and case
•  Case weight
•  Delivery schedule
• The cost of the product
• The inventory turn

The article also emphasize on the limits of the DPP analysis:” There are limitations to the use of DPP. Since DPP is a cost oriented approach to merchandising decision making, it does not take into account the consumer’s changing tastes or attitudes. The analysis also does not report how much shelf space should be changed. This problem is being addressed by the shelf space. One of these measures is the DPP of individual products. The integration of DPP and shelf allocation systems opens many possibilities for the effective management of grocery merchandising”.

The strategic approach of DPP

The article proposes a chart to charecterize the strategic interest of one product by its DPP.

Here is an example of how it works, and the axis of this strategy.

I also reconstructed a chart based on the same principle, with the same figures, to show how concretely we may picture the analysis. I have put the size of the circles by the size of the DPP/week.

Here are some charts showing the results of the study. It shows how to implement the technique.

I believe that this analysis may help to have a better view also about how to optimize the costs of goods sold in order to optimize profitability of product range.

Once again, DPP should not be taken solely, and you need to have a real category management strategy to properly manage your product selection.

Category Management & Direct Profit by Products: When product complexity hurts true profitability

I wanted to share with you an interesting document I found wrote by Accenture. It is directly linked to my previous post about the Direct Profit by Product Analysis. This document is Named "When Product Complexity Hurts True Profitability". 

This concept is very true especially in category management in the FMCG world. As the article points out, the number of Skus in product range is constantly growing. It is actually growing faster than the sales do, which means the sales/product figures are declining fast. That means categories are losing efficiency.

Moreover, the more product you retail the more costs will be implied in your activities. That means more room in your warehouse, more data to analyze and to deal with for accountability and management, more time spent to set up products on shelves. More products mean more sales, but don't mean more profits in the end for sure.

The article emphasizes that there is a need to understand hence this complexity and its impact on the cost of goods sold, and therefore the profitability. Hence you need to track all the costs linked to one product. As the article says:
 These include direct labor and materials costs, administrative and sales expenses, rebates, discounts,
supplier overpayments, an allocated portion of the company’s cost of capital, and whatever other charges and expenditures the company makes related to the product.

Accenture analysis reveals that most blue-chip companies have about 65 percent of their revenues tied up in their cost of goods sold (COGS). Of that, more than 80 percent is for direct material costs. Clearly, if firms hope to improve a product’s profitability, COGS is where to start.

Winners and losers
In the example below, Product A is a typical underperforming product, with high direct costs. Even though the indirect costs are fairly low, Product A would typically be eliminated as both the true margin contribution and the sales volume are low. However, if the product is strategically
important—such as a legacy product—or has development potential, that has to be
taken into consideration.
Product B is a typical high performer. Direct costs are low, and even though indirect
costs are fairly high, the true profit margin is still high. The product’s sales volume
is above average but not as high as you would want with a high true profit product.
This means that Product B is a good candidate for a more focused sales effort.
Product N is a typical representative for true profitability improvement potential;
generally this type of product accounts for a large portion of a company’s product
portfolio. The true profit margin is rather low, but sales volume is high. The product
could benefit from product reengineering and design-for-assembly to minimize
the direct materials and labor costs.

These kind of analysis are I believe very interesting in terms of category management. What is also very interesting with this analysis is that it may evolves not only depending on the negociation of the gross sales price, but could evolve depending on the work ones may do on some part of the costs of good sold.

I believe that these approach will tend to become the norm, sooner or later.

Category Management and #Retail: Working on the Direct Product Profitability #DPP

I have already discussed not so long a go about a great technique to leverage a category profitability by analyzing the Cost of Goods Sold, I wanted to discuss another key concept on how you should analyse profitability in retail nowadays. Indeed, gross margin is probably the most common KPI of profitability used in retailing, but it does not give you the whole picture. 

Here is a great chart that will show you why:

In the chart you will find 5 different products, with different features. Depending on the KPIs you will look at, you will have a different prospective of what the performance of the products are.

If you look at Item A, it is the Item with the higher % of gross margin, which you may think is cool. But when you take into account all the direct product costs (DPC), which includes supply chain, wages, among others, you find out that you are loosing money on it.

Same thing about with Item E: You sell it the most, and despite a low % of mergin, it is the product that provides you the most gross margin at the end of the week (isn't it the concept of FMCG?). But at the end of the day, the resources required to retail the products are so big that the direct profit is negative.

In this example, it is the product C that is the most efficient and profitable. It doesn't have the best sales, it doesn't have the best % of gross margin, neither is it the most expensive, but the way its cost of goods sold is designed and how it performs makes it by such an analyzis the perfect deal.

The Direct Product Profitability modell allows you to make such an analysis. Its uses is common in companies like Walmart.

I believe that Direct Product Profitability is obviously by far the best way to analyze one product performance. Obviously, there may be other variables that are not taken into account, as the modell is more used for a purchasing strategy than an actual category management strategy. I believe that you should take into account the penetration rate of the product, or its loyalty rate, in order to understand how strategical the product maybe in your product range.

Here are The Seven Step DPP process

The DPP model is capable of calculating net profitability of individual items of fast moving consumer goods. Working with the DPP model is a seven-step process:

1. DPP model fine tuning: the classical DPP model is adapted to specific product characteristics of your industry
2. Input of process characteristics: process characteristics of the logistics chain are entered as activity drivers in the DPP model (examples: delivery frequency, productivity ratios)
3. Input of general ledger resource costs: resource costs of the central depot, transportation and the store (examples: transportation cost per km, costs per working hour)
4. Calculation of activity costs: activity costs are calculated in the DPP model
5. Input of product characteristics: all characteristics of individual products are entered as cost drivers
6. Calculation of direct product costs: activity costs are allocated to products
7. Calculation and presentation of direct product profitability ratios