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Unit4, a Netherlands-based vendor of financial management software focused mainly on midsize companies, recently acquired prevero, a German vendor of performance management and business intelligence software. The acquisition reflects a convergence of transactional and analytic business applications, which I have written about. ERP and financial management software vendors increasingly are adding analytic capabilities – especially in financial performance management (FPM) – to the core functions of transaction processing and accounting to broaden the scope of their offerings.
For users of finance software the addition of analytic capabilities makes it easier to obtain useful information directly from their ERP system. Our Office of Finance benchmark research finds that companies are split on information availability: Half (50%) of participants said that it’s easy or very easy to get information from their ERP system, but nearly as many (48%) said it isn’t easy. One benefit of having analytics built into a transaction system such as ERP or financial management is that it automates and therefore often speeds up the transformation of data that’s collected into useful, digestible information. Our next-generation finance analytics research finds a tangible business benefit in doing this. Nearly all (86%) companies that said they have up-to-date data also said they are able to respond to changes in business conditions in a coordinated fashion, compared to 38 percent in companies that said that most (but not all) data is current and just 19 percent of those whose data is less than up-to-date. From the vendors’ perspective, the integration of the two categories helps them increase revenue from customers, differentiate their offerings in a highly commoditized market and enhance the “stickiness” of the software by increasing the number of process and user touch points in customer organizations.
Midsize companies have essentially the same capability requirements as larger enterprises, but they typically have less money and fewer IT resources to acquire and maintain business software. Vendors that focus on this market segment have sought to respond to this situation by enabling specific types of businesses to cut implementation times and simplify maintenance. In Unit4’s case these categories include business and professional services, higher education, nonprofit and government. Cloud-based applications sold as a service address the cost and IT resource challenges better than on-premises systems by cutting the initial investment and eliminating the need for internal staff to manage the software. Integrating FPM software adds substantial value because it greatly simplifies the process of getting useful information out of the ERP system (in the forms of reports, up-to-the-minute dashboards and scorecards) as well as planning, budgeting and statutory consolidations that interact with the transactions systems. This is important for business and professional services companies, which need to minimize administrative staff, and to higher education, non-profits and government agencies, which have limited operating budgets and historically have had a hard time attracting IT talent.
The Prevero acquisition is a strategic step for Unit4 since it is likely the most cost-effective approach to adding analytics (including purpose-built predictive analytics) and FPM to its financial management offerings. This purchase has the potential of increasing the company’s annual recurring revenue for new and existing customers, and in any case, it will increasingly become necessary for any vendor to be competitive in the ERP and financial management categories. Prevero’s project management capabilities also are a good fit for Unit4’s professional services vertical and a useful feature for bridging annual budgeting and long-term planning, in which projects and major initiatives can span multiple fiscal years.
Practically speaking, however, Unit4 faces several challenges in challenges in absorbing prevero, beginning with integration of the software. Initially it can be easier to achieve a workable integration of cloud-based products than on-premises ones, but shortcuts may not eliminate the need for more comprehensive changes over the longer term. This is especially important for creating offerings tailored to the specific needs of targeted industries. For example, Prevero’s user interface is adequate today but will require significant updating to remain competitive. Although the two product lines are a great fit, financial management and FPM have different audiences in the buying process (even if the CFO and the controller are important in making the ultimate decision for both). Additionally, Unit4 will need to devise and implement sales training and marketing programs for effective cross-selling. Furthermore, part of Unit4’s growth strategy is to expand its presence in the North American market, but Prevero’s customers are mainly in Europe, and there are subtle but important cultural differences between the two (for instance, in attitudes toward the budgeting process) that will have to be addressed in localization of the software.
Nevertheless, bringing integrated FPM and analytics capabilities to Unit4’s financial management software can benefit both current and potential customers. I recommend that they monitor the product roadmap closely to understand when specific capabilities will become available. Prevero’s customers are likely to benefit from the investments that Unit4 will make in the software generally and the user experience in particular. At the same time, there are always uncertainties when any software company is acquired. Interested parties should watch how Unit4 addresses them over the coming year by clearly communicating its intentions and progress to these objectives.
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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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