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        Robert Kugel's Analyst Perspectives

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        Profitability Management vs. Managing Profitability

        Pricing and profit margins appear to be trending topics, which is normal at this stage of the business cycle. North American companies achieved high levels of profitability coming out of the last recession by staying lean, but this trend has run its course. Margins are being squeezed, and companies are looking for ways to add to the bottom line.

        In my terminology, “managing profitability,” which is what most companies do, is not the same as “profitability management.” The latter will give a corporation a long-term advantage over competitors that simply manage profitability because it almost always provides a better balance of the trade-offs between revenue and market share objectives and profit goals within other essential business constraints (such as operating in a legal, ethical and sustainable fashion).

        Managing profitability is a workable but simplistic approach that seeks to maximize revenues and minimize costs. The practice is attractive because it’s straightforward, but by itself, maximizing revenue is rarely optimal in today’s complex business environment. Companies usually do not explicitly consider margin in establishing sales targets. Neither do they always measure costs properly, in a way to make the best economic decisions in setting revenue goals and sales quotas. Maximizing revenues is the wrong approach if the mix of sales is more heavily weighted to low-margin products or if the products consume a disproportionate share of a scarce resource, such as time used on an expensive machine tool.

        Profitability management has been possible but until recently not really practical, which explains why it is not more widely practiced in most types of business. Software that facilitates the analyses needed to perform profitability management has been available but not widely adopted, in part because it has not been easy enough to use in day-to-day operations. And although profitability management is the norm in some businesses, such as airlines and hotels, it is still a novel approach in most others. Consequently, so far there haven’t been enough success stories to spur senior executives to change.

        Price optimization, which I covered in an earlier research perspective, can be described as surfing the demand curve. Rather than setting a single price, companies use segmentation techniques to assess buyers’ price elasticity to set the highest price that has the greatest likelihood of completing a sale. Thus, a company trying to maximize market share will be willing to accept lower prices from any type of buyer, while those companies focusing on profitability will be more discriminating to achieve a higher average price. Such optimization usually requires analytic software to handle the mass of data necessary to identify relevant and valid buyer segments and calculate their elasticity on an ongoing, dynamic basis. The rise in retailing on the Internet is enabling greater use of price optimization, since sellers can easily present different prices to potential buyers using a variety of techniques.

        Price optimization alone works best in situations where the marginal cost of sales is essentially the same for each unit. This is the case in travel, hospitality and most other finite inventory product categories. (“Finite” is a term of art used to distinguish time- or date-specific goods such as airplane reservations or hotel beds that disappear if not used, or fashion or other goods that have limited production or quickly become obsolete.) This type of optimization is also used in financial services, where the cost of funds for a given asset class will be identical.

        One specialized form of price optimization is managing discounts, which is used by bricks-and-mortar retailers because they are able to display only a single price to all prospective customers. Since they have no way of knowing or testing the elasticity of demand of potential buyers, they use software to carefully monitor sales data and inventories to manage price markdowns. This approach is especially useful for seasonal items or fashion because such goods become obsolete in a relatively short period of time. Segmentation is achieved mainly on how much the purchaser values novelty, selection, immediate gratification or convenience.

        The difference between price optimization and revenue optimization (as I use the terms) is that revenue optimization explicitly considers the profitability of sales in making trade-offs to determine how much to sell at which price. For companies that offer goods and services with different degrees of profitability, revenue optimization usually works better than price optimization alone. Indeed, revenue optimization can improve bottom lines even without adopting price optimization.

        Accurate optimization of revenue requires an accurate measurement of costs. Too often, companies do not gauge product margins accurately. They may use static assumptions about margins or employ standard cost accounting methods, which often do not measure the true economic costs. Several costing methodologies have emerged over the past half century that are designed to give companies better ways to measure costs, including activity-based costingmarginal planned cost accountingresource consumption accounting and lean accounting, to name four of the most common. An alternative approach that can be used with any costing method is a time-based optimization technique (although the more accurate the costing method employed, the better the results will be). A time-based approach is especially useful for any asset-intensive business.

        Most businesses sell multiple products and/or services, and in most cases each of these has different degrees of profitability. Since organizations have finite resources, they need to allocate them to generate the optimal profit margins given market demand and other factors. Here again, optimal is not necessarily the maximum, because pricing and production decisions are usually constrained by market demand (not everyone wants a premium widget) or by strategy (such as an objective of increasing market share in some low-margin segment or using discounts to undermine the profitability of a competitor’s key product). “Optimal” is a temporary condition that changes according to demand, costs and market conditions, to name three key factors. Thus, because of the complexity of dealing with large, complex and changing data sets, a dedicated software application almost always provides a corporation with a greater ability to frequently recalculate optimal solutions and analyze their impact, compared with manual or desktop spreadsheet-based systems.

        Profitability management is still in its infancy in many businesses. It is a departure from tried-and-true approaches, requiring a change management effort applied across the organization. It therefore requires focus from the CEO and senior executives to be implemented successfully. Price and revenue optimization software is a necessary component in profitability management. And as I recently noted, its impact can be amplified when it is used in connection with complementary software, such as that designed for sales and operations planning, sales incentive management and performance management. The recent increase in management’s focus on profitability is likely to spur increased adoption of profitability management techniques and software that will allow companies to operate more effectively, not just efficiently, so that higher margins become more sustainable.


        Robert Kugel – SVP Research


        Robert Kugel
        Executive Director, Business Research

        Robert Kugel leads business software research for Ventana Research, now part of ISG. His team covers technology and applications spanning front- and back-office enterprise functions, and he personally runs the Office of Finance area of expertise. Rob is a CFA charter holder and a published author and thought leader on integrated business planning (IBP).


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