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Information technology enables a data-driven management style that was not feasible until powerful, affordable computers became generally available. There’s no bright line marking when this became possible; the process is ongoing. People were using financial analytics long before ENIAC, the first general-purpose computer, appeared, but the metrics available were not especially timely, broadly applicable to day-to-day situations or comprehensive enough to inform most management decision-making. Even today, there are many areas of business management where companies continue to operate much as they have in the past. One of those is pricing.
Pricing strategies are important because they can have a disproportionate impact (positive and negative) on a company’s bottom line. Managing prices has always been an activity of keen interest, but it has become even more so over the past decade as a result of the constrained pricing environment. In particular the importance of linking pricing to demand has increased. As its name suggests, demand-based pricing is a method that uses the buyer’s demand, based on an estimate of the perceived value of goods or services to the buyer, as the central element in setting an optimal price. Optimal in the sense that it best supports a company’s product and sales strategies; one may wish to be a high-volume, low-price leader while another aims to sell a premium-priced product or service to a specific market segment.
Price and revenue optimization (PRO) is a business discipline used to effect demand-based pricing; it applies market segmentation techniques to achieve strategic objectives such as increased profitability or greater market share. PRO first came into wide use in the airline and hospitality industries in the 1980s as a way of maximizing returns from less flexible travelers (such as people on business trips) while minimizing the unsold inventory by selling incremental seats on flights or hotel room nights at discounted prices to more discretionary buyers (typically vacationers). Today, it is a well-developed part of any business strategy in the travel industry and increasingly used in others.
One reason why transportation and hospitality were early adopters of PRO is that these businesses had access to large data sets on which to base their pricing models and pricing decisions as well as a strong motivation to utilize this technique. (In the case of the major airlines it was the need to be able to offer a limited supply of budget fares to compete with low-cost carriers.) The application of analytics to pricing has spread since the 1980s as other industries have accumulated large-enough data sets to analyze and acquired the computing power and tools to analyze them. Our benchmark research on big data shows that three-fourths of companies are addressing more than 10 gigabytes of data per day and 10 percent are already dealing with a terabyte or more. They need to sift through large data sets to collect buyer behavior characteristics that will enable them to quantify how best to present the offer to each type of prospective customer.
The methodology used in presenting an offer varies by industry because of limitations in the data available to a particular type of business. For example, Web-based consumer businesses attempt to gauge a buyer’s price elasticity based on readily observable demographic characteristics. (One example would be charging Apple computer owners more on the theory that they were able or willing to pay more.) Financial services companies have access to large and rich data sets that provide insight into customer behavior on which to build their price elasticity models. In bricks-and-mortar retailing, buyers are anonymous, so markdown management software must utilize actual sales and inventory data (by definition, things that aren’t selling according to plan are overpriced) and other characteristics (store location and weather, for example) to adjust prices in response to actual demand. In business-to-business selling, disaggregating features and services and then tailoring a mix of these features and services at a range of prices for each is a common approach to optimizing results.
Initially some companies built their own models, but adoption of price and revenue optimization has grown as commercial software has become available. These applications apply complex analytical models and business process management. While software is the key to enabling optimization, success also demands changes in management practices. Frequently the guidance provided by a model runs counter to established practices. For example, in the case of seasonal items in retailing, a couple of small, early price reductions generates more revenue and lower markdown costs than a big percentage cut later to clear unsold merchandise. Financial services companies can charge some of their best customers more because doing so doesn’t have a negative impact on their behavior.
Because a data-driven approach to pricing often goes against the grain of “what everyone knows” and may have a negative impact on some roles or functions in a business, change management is necessary to make the adoption of price and revenue optimization a success. I’ve identified six components that corporations must consider and manage well to be effective in using PRO: strategy, external factors, people, process, information and technology (software). Here are some thoughts on each of them.
Above all, companies must have a realistic pricing strategy that is closely aligned with their capabilities, product strategy and competitive position. In a scale-driven business, for instance, it probably doesn’t make sense for a small player to try to be the low-cost provider. Instead, pricing software enables these companies to find ways to maximize pricing in a price-conscious market by designing offerings with valued features and services that add to their margin.
Pricing strategy and execution must take into account external factors. In particular, different cultures and businesses often have their own attitudes toward fixed and negotiated pricing. In some cases, especially in consumer markets where fixed prices have been the norm, people may consider price optimization unfair. Companies that try to implement a PRO strategy must realize that they may encounter resistance and be careful in how their marketing and communications position their approach to pricing. That noted, despite some annoyance, people have grown accustomed to highly variable pricing by airlines and hotels. Also, there may be legal and regulatory issues that impinge on a company’s pricing flexibility.
As to the people dimension, management needs to ensure that the internal groups involved in pricing are behind the effort. It’s extremely important to align incentives (especially sales compensation) with the price optimization objectives. In many cases, ongoing training will be necessary to continually refine techniques and deal with issues that arise. For some organizations, a “center of pricing excellence” may be a useful way to build on its experience and entrench a culture of price optimization. Exactly how this is handled depends on whether the company has a centralized or decentralized structure to manage pricing.
People and process meet in the ongoing evaluation of price-setting practices by a cross-functional team that incorporates all stakeholders. Initially these people will meet frequently (at least once a month), but it may require only quarterly review as PRO matures. There also must be a well-defined price analytics review process to ensure the methodologies the company is using are sound.
Easy, rapid access to the data needed to support the use of pricing algorithms is a prerequisite for successful implementation of a pricing strategy. Such data feeds the analytics and facilitates rapid pricing-decision cycles. Our research consistently shows that access to the appropriate data is an issue for a majority of companies and that this issue grows in proportion to the company’s size.
Lastly, the company must acquire the right software, implement it properly and tailor it to its needs; it also should be easy to deploy, use and maintain. When it comes to pricing, there can be subtle differences in the needs of particular types of business; prospective buyers should focus on vendors that have strong references in their specific industry.
I recommend that all companies investigate how they can use price and revenue optimization in their business. There are plenty of data and capable analytical tools to help them achieve greater revenue, larger margins or both. Especially in slow growth economies this can be a winning strategy.
Senior Vice President Research
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There were two noteworthy themes in SAP CEO Bill McDermott’s keynote at this year’s Sapphire conference. One was customer assurance; that is, placing greater emphasis on making the implementation of even complex business software more predictable and less of an effort. This theme reflects the maturing of the enterprise applications business as it transitions from producing highly customized software to providing configurable, off-the-rack purchases. Implementing ERP will never be simple, as I have noted, but as companies increasingly adopt multitenant software as a service (SaaS), vendors will need to make their implementations as repeatable as possible and enable flexible configuration of parameters and processes that substantially reduce the billable hours required to complete a deployment. “Customer assurance” is an important stake in the ground, but it will be an empty concept unless there is complete overhaul of the entire value chain to take it beyond good intentions. Otherwise, customer assurance will be an ongoing rearguard action to overcome technology-driven challenges and disincentives for improvement. Business applications must be re-engineered to facilitate implementation, substantially reduce the likelihood of implementation errors and facilitate subsequent changes to adapt to changing business conditions. Moreover, software vendors’ partners will need to demonstrate that they can reliably cut a substantial number of billable hours per implementation engagement. This will require partners to restructure their business models. Neither of these changes will be easy to accomplish. To its credit SAP has set a course for increasing the simplicity of using its core ERP and financial management software. Getting there soon would greatly enhance its ability to retain if not gain customers in these mature markets.
McDermott’s second notable touch point was the “digital boardroom,” a wall-size set of monitors displaying a broad array of current company data (including some in real time) in easy-to-understand visualizations and in alphanumeric format. The digital boardroom demonstration contained not just the standard set of drill-down and drill-around capabilities but also the ability to work interactively with data to do what-if scenario planning and analysis. While some might view it as only eye candy, the immediacy of the data and the ability explore potential outcomes based on different conditions or actions would represent a substantial breakthrough in the use of data and analytics by senior executives.
The idea behind the digital boardroom is sound: Boards of directors, executives and management need up-to-date information to help them understand the current state of the business, its opportunities and challenges. However, in our benchmark research on the Office of Finance fewer than one-third of companies said that the information they receive is timely. In the past, somewhat timely information might have been the best one could expect but no longer. Analyses and plans based on out-of-date information may not be actionable. However, the business value of the digital boardroom will be an empty promise unless companies address the root causes of the timeliness issue. They include scattered information, a heavy dependence on desktop spreadsheets for aggregating and analyzing data, and limited penetration of advanced analytics. Our research also shows that fewer than half of finance departments use relatively straightforward analytic techniques such as product and customer profitability, only 22 percent employ economic and market data and trends in their analysis, and just 12 percent use predictive analytics. SAP’s existing and planned software can help address these shortcomings, but it cannot overcome the data management issues that prevent companies from having timely information or the lack of analytical skills and training that also hamper a company’s ability to present incisive, action-oriented analyses and prescriptive models in a digital boardroom.
One of SAP’s objectives in demonstrating the digital boardroom is to make senior executives aware of what’s possible. Ideally this would be a potent source of “demand pull” – directives from the top to enhance a company’s systems and modeling capabilities by addressing data, training, process and systems requirements. SAP’s enterprise software generally and its Universal Journal in particular can begin to address the technology and some of the data issues. But experience makes me reluctant to assume the best. It seems likely that for the time being the numbers and analyses that wind up being displayed in a digital boardroom will be created using the same crude, time-consuming methods. Our next-generation finance analytics research finds that two-thirds (68%) of individuals spend the greatest amount of their time on data-related tasks in preparing for analysis while only 28 percent are able to focus on the analysis itself. One can hope that data environments will improve and that users will switch to dedicated analytic software from desktop spreadsheets, but applications vendors should focus on adapting to shoddy IT environments rather than hoping that customers will change their behavior. SAP also will need to ensure that the full range of its analytics and business intelligence software is readily integrated with the digital boardroom. Doing this must include its newly acquired technology from Roambi, which provides mobile support for smartphones and tablets.
The ERP and financial management software categories are currently in a process of transformation, as I have written, one that will be as sweeping as the shift to client/server applications in the 1990s. The trend to cloud-based multitenant architectures gets the most attention, but real-time information availability, a more productive and pleasant user experience, improved in-context collaboration and a lower total lifetime cost of ownership will be key factors in determining winners and losers. Aware that they are vulnerable to disruption, established vendors – including SAP – have been adapting. Statements of direction are useful for communicating with customers and the market generally. However, SAP needs to accelerate its pace of development to arrive at the transformed state it promises if it is to remain competitive.
Senior Vice President Research