What are Bad Profits?

Yesterday, I had a lengthy conversation with the Vice President of Finance of a major company. He was immersed in the capital budgeting process, and wanted to discuss ways to evaluate investment proposals.

Our conversation started with a discussion of the cost of capital, which is an important ingredient in evaluating investments. After all, what could be more logical than ranking investment opportunities by their projected returns, taking into account the cost of capital, and putting money into the most lucrative opportunities?

In my writing, I argue that all revenues are not equally desirable – some produce high profits, and some actually produce losses. Profitability management is all about figuring out which is which, and how to get more profits from an existing business.

But are all profits equally desirable?

The answer is no – and the key to understanding the difference between “good profits” and “bad profits” is the Investment Decision Matrix, pictured below.

The desirability of an investment is not just a function of the likely returns, but also and more importantly, the strategic relevance (whether the investment moves the company’s strategy forward).

Two quadrants of the matrix are easy, the other two take some thought. Let’s start with the easy ones. The upper right, high returns and high strategic relevance, is an obvious winner. The lower left, low returns and low strategic relevance, is a pretty poor bet.

Think about the upper left, high returns but low strategic relevance. This quadrant is quicksand. These investments look very attractive, but take the company’s capital and focus away from its main line of business. All too many companies have unclear and unproductive positioning because they lack the discipline to say no to attractive-looking investments that don’t fit. Ultimately, companies that do this get picked off by highly-focused competitors. These are the investments that produce “bad profits.”

Let’s look at the lower right, low returns but high strategic relevance. These are investments that would show up at the bottom of a simple capital budgeting ranking, but are essential to moving the company forward. Here, the watchword is “courage.”

For example, I remember meeting with the top officers of a major telecom company several years ago when telecom companies first began to develop video capabilities that could compete with cable TV. The company had a study that showed that an early investment in video would not pass the company’s investment hurdle rate. The question was whether to invest.

After discussion, the officers saw that the real question was not whether this initial video investment produced high enough returns. Rather the right question was whether the company was willing to remain the dominant communications channel into millions of customers, or whether it was willing to open the door for a host of competitors to get a foothold in all of their customers. Fortunately, the management team made the right decision.

The moral of the story: If investments in the upper left quadrant produce “bad profits,” investments in the lower right produce “good losses.”

How is this possible? Investments are virtually always part of larger business or strategic initiatives. The correct frame of analysis is the overall initiative, not just the component investment.

Within this strategic context, capital budgeting is a useful way to evaluate alternative ways to accomplish a strategic goal (e.g. which machine to choose), but you can’t use capital budgeting to determine strategy.

This is why it is so important that CFOs and other top finance managers be broad-gauge strategic thinkers, as well as disciplined business managers. Their company’s future depends on it.

What's Wrong With a 95% Service Level?

Customer service level is a core measure of company performance. This measure seems completely obvious: after all, if you increase your line-fill or case-fill from 94% to 96%, your customers will surely be much more satisfied. And satisfied customers will buy more from you, increasing your profits. Right?

This seemingly simple logic has critical flaws that are very important for your company. Is your objective simply to maximize average customer satisfaction? Or is your objective to maximize your company’s profitability and growth? These are not necessarily, or even often, linked.

Think about the following questions, in the context of a company with a 95% service level.

• Which customers get the bad 5% of your service measure? How would you feel if your best customers – the customers in your company’s “sweet spot” (those that produce the most profit and have the highest growth potential) – received unreliable service 10% of the time, while your marginal customers enjoyed 99% service? How would you feel if both your best customers and your marginal accounts received the same poor service 5% of the time – after all, this is what the measure indicates.

• How bad is the 5% deficiency? Is it hitting key customers running a VMI or cross-dock system with one week delays, or is it hitting customers carrying ample inventories with an overnight delay? Is it hitting critical products or commodity-like products with many substitutes?

• What price are you paying for making promises you can’t keep? If you always made realistic customer service (order cycle) promises that you could keep virtually 100% of the time, would your customers trust you with a slightly longer order cycle, or are they simply insisting on very tight cycles to give themselves “breathing room” for your service deficiencies?

When you focus on aggregate measures of customer service, in reality you are maximizing what’s easiest to measure, not what gives you the most profitability and lucrative growth. This is another artifact of the Age of Mass Markets, when companies distributed as widely as possible, customers had plenty of inventory, and computers were in their infancy.

Service differentiation is a much more effective way to frame and measure customer service. In a nutshell, you should make different order cycle promises to different customers depending on your customer relationship and the nature of the product.

Consider a simple 2x2 matrix, with core and non-core customers, and core and non-core products. A core customer is a significant steady customer, often one whose supply chain is integrated with yours. A non-core customer is a smaller, occasional customer, or even a large, high-potential customer that uses your competitor as its primary supplier. A core product is either a high-volume product or a critical product with no substitutes. A non-core product is a slow-moving product, not critical, and often with ample substitutes.

If you think about each quadrant of the matrix, it becomes clear that each quadrant’s customer/product characteristics logically suggest a different order cycle.

The core-core quadrant requires fast, completely-reliable service, and here a 95% service level is particularly deadly. For non-core customers ordering core products, you might offer guaranteed 2-3 day service, but always keep your promises. This will allow you to produce 100% reliable fast service for your core customers (from local stock), while gaining the leeway to source product from centralized stock to meet the occasional spikes in demand that non-core customers sometimes produce with occasional large orders. The alternative is to carry a huge amount of costly safety stock in the effort to treat all customers the same.

There are important exceptions. If a non-core customer is a high-potential account that a sales rep is working intensively, it can be bumped into the core category, as long as you reexamine this after a period to see whether the relationship has changed.

The service differentiation logic is similar for your non-core products. By definition, non-core products are those not needed urgently. When a core customer orders a non-core product, most of the time it can be sourced from local stock, with an order cycle of perhaps 1-2 days.

The big cost drain occurs when non-core customers order non-core products. Here, you will need a massive amount of local safety stock to meet an aggregate measure like 95% service level (with short cycle time). The correct course is to make an order cycle promise of perhaps 3-4 days, so you can source the product from a centralized pooled inventory.

Three important customer service principles emerge: (1) you should match your order cycle promise to the nature of the customer relationship and the product characteristics; (2) you should make different promises to different segments of customers for different segments of products; and (3) most importantly, you should always keep your promises.

The right measure of customer service is not aggregate line-fill and case-fill: it is always keeping your promises. Service differentiation will enable you to maximize your profitability and to develop high sustainable profitable growth. The classic dilemma of trading off between cost and service is an obsolete, misleading concept. It assumes that all customers and products are the same.

You can have your cake and eat it too if you have clarity, focus, and follow-through – and you let go of the tacit goal of trying to be everything to everyone.

Think about another common measure of customer satisfaction: net promoter score. This is a commonly-used measure that compares customers who would recommend you against customers who would not. The problem is that this is another aggregate measure with all the flaws of an overall measure of customer service level.  (Aggregate surveyed customer satisfaction has the same problem.) Clearly, the customers in your “sweet spot” should have net promoter scores off the charts, or your islands of profit will be sinking beneath the waves.

What about the rest of your customers? If you implement service differentiation effectively, they should also have a very high net promoter score. They will have a clear understanding of their relationship with you, they will trust you to always keep your promises, and they will know exactly what they have to do to change their relationship and therefore their order cycle.

In business, the worst news is not knowing what to expect.

Three Missing Steps in Supply Chain Optimization

I just finished an interview with a journalist who is writing on the importance of supply chain optimization. This writer is addressing a set of distributors of products that have relatively low value for their weight and volume. This makes supply chain costs really critical to their profitability.

As I thought about the topic, it struck me that there are two very different ways to approach the problem. The traditional way is to assess the software and automation possibilities that could be deployed, and then to think about ways to get the operating personnel to “buy into” the solution. I could visualize the usual checklists of software packages and capabilities.

Certainly, a number of terrific software packages and warehouse automation systems have been developed, tested, and put into widespread use. But the real question is what to do with them.

In this slow economy, customers are minimizing their inventory, and increasingly depending on distributors for fast service. This enables strong distributors to increase business, but it also places a big cost burden on them. In the particular industry the journalist was writing about, this cost dynamic was having an extremely strong impact on profitability.

When I considered the deeper question of how to optimize this supply chain, three steps seemed especially important – steps that are all too often left out of the process.

First. Divide the business (logically) into core and non-core customers, and core and non-core products. Usually, your core customers and products are characterized by high-volume. If you think of this as a 2x2 matrix, each quadrant has very different characteristics, and each requires a different supply chain.

For example, core products for core customers should flow like a river from suppliers through distributors to customers, with minimal inventory (relative to sales) and minimized handling. Think about how radically this differs from core products sold to occasional customers, or from non-core (sporadically-ordered) products even sold to core customers.

The most important initial step in optimizing a supply chain is to understand that the right supply chain solution (decision rules, inventory levels, physical process) for each quadrant can and should be very different.

Second. Work with your customers – especially your core customers. Many customers do not have a sophisticated knowledge of how to set inventory levels and reorder patterns. You can make a big difference in both your profitability and your customers’ profitability by helping them. This is especially critical in these difficult times.

I recall working with a major distributor a number of years ago to reduce supply chain costs. After a little investigation, we figured out that there were only three or four inventory/replenishment systems that the customers used, and that most customers did not know how to keep them set correctly. We created a small team that worked with the core customers to readjust their systems. After a month or two, the cost savings were surprisingly large.

Third. Get the sales reps involved. In most distribution businesses, the sales reps are the primary link to the customers. In my experience, sales reps in many companies have an overwhelming number of objectives, ranging from revenues to promotional programs to brand introductions to point-of-purchase displays. While some companies include gross margin in sales objectives, net profitability, per se, is almost never an objective.

In many distribution businesses, supply chain costs are a critical determinant of profitability. These costs can vary considerably from customer to customer and product to product. They are deductions from gross margin in profitability calculations, so a simple focus on gross margin eliminates a major source of profit improvement.

It is very important for the sales force to understand the profit impact of customer orders and other supply chain costs, and to be given a fairly simple program to selectively improve customer profitability. Here, creating a simple “red-yellow-green” color-coding designation can provide terrific results.

For a sales force to be productive, the reps must have at most 3-4 clearly understood objectives. Profitability maximization must be one of them.

All too often, managers instinctively reach first for technology solutions, focusing primarily on the selection and implementation processes. But the real profit impact comes from changing the business.