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August 13, 2015 in Big Data, Business Analytics, Business Collaboration, Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Information Management (IM), Operational Performance Management (OPM), Sales Performance Management (SPM), Social Media, Supply Chain Performance Management (SCPM) | Tags: Analytics, Performance Management, Price optimization | by Ventana Research | Leave a comment
Optimization is the application of algorithms to sets of data to guide executives and managers in making the best decisions. It’s a trending topic because using optimization technologies and techniques to better manage a variety of day-to-day business issues is becoming easier. I expect optimization, once the preserve of data scientists and operations research specialists will become mainstream in general purpose business analytics over the next five years.
Optimization was first adopted by businesses in the middle of the 20th century, aided by the introduction of digital computers. The first technique that gained broad for a few specific purposes was linear programming, one of the most basic optimization methods. Linear programming enables analysts to quickly determine how to achieve the best outcome (such as maximum unit volume or lowest cost) in a given situation. They do so using a mathematical model that captures the key variables that go into the decision and any constraints that may affect that decision. A food processor, for instance, may use three types of cooking oil to make a product. To maximize its profit, the company needs to determine the exact proportions of the three oils that result in the lowest production cost. However, it can’t just choose the cheapest of the three in every case because for flavor and shelf-life requirements there’s a limit to the maximum percentage of each oil that it can use. Linear programming using the simplex algorithm quickly solves the problem.
As computing capabilities became increasingly affordable, companies could use more complex algorithms to handle ever more difficult optimization problems. For instance, the airline industry used it to determine how best to route aircraft between two cities and to staff flight crews. Not only can software find the best solution for scheduling these assets in advance, it also can rapidly re-optimize the solution when weather or mechanical issues force a change in how aircraft and crews are deployed. Airlines were also in the vanguard in the 1980s when they started using revenue management techniques. In this case, the optimization process was designed to enable established airlines to compete against low-cost startups. Revenue management enabled the large carriers to offer low fares to price-sensitive but flexible vacationers without sacrificing the higher fares that the less flexible businesspeople were willing to spend. The same approach was adopted by hotels in pricing their rooms. Starting in the 1990s markdown management software, which I have written about gained ground. It enables retailers to make more intelligent pricing decisions by monitoring the velocity of purchases of specific items and adjusting prices to maximize revenue. To be feasible, each of these optimization problems require large data sets and sufficient raw computing power.
We’re now on the cusp of “democratizing” what I call optimization analytics. Big data technologies are making it feasible and affordable for even midsize companies to work with much larger data sets than they have been able to in the past. Our benchmark research on big data analytics finds that about half of participating companies already use analytics with big data. This is partly the result of more powerful and affordable data processing resources but also because companies have invested in systems to automate many functions. The rich data sets created by these business applications provide corporations with the raw material for analysis. This data has the potential to enable businesses to make more intelligent decisions. From a practical standpoint, though, the value of these large data sets can only be realized by moving optimization analytics out of the exclusive realm of data scientists and into the hands of business analysts. These analysts are the ones who have a sufficient understanding of the business and the subtleties of the data to find useful and repeatable optimization opportunities. Three-fourths of companies in our research said that they need these business skills (“domain expertise”) to use big data analytics successfully.
Optimization analytics is a breakthrough technology with the potential to improve business performance and create a competitive advantage. You can’t do optimization in your head, and it’s not feasible in desktop spreadsheets for anything but the most basic use cases, such as linear programming optimizations on relatively small data sets. This is a good reason for almost any company to consider adopting optimization software.
Another reason why companies will find it attractive to apply optimization analytics broadly is that the results of applying optimization routines may be superior to using common rules of thumb or relying on instinct and experience. One of the most important lessons for executives about optimization analytics is that optimal solutions are sometimes (but – crucially – not always) counterintuitive to established norms. For instance, in markdown management, retailers often have found that smaller, more frequent price reductions maximize profits and produce a considerable improvement in sales over the end-of-the-season price slashing that was once considered to be the best practice. In financial services, charging your best customers more for loans and other services turns out to be the optimal choice for the bottom line of financial institutions. Another important insight from our collective experience with optimization is that while the value of these analytics as realized in a single event or transaction may be small, it can have a measurable impact on profitability and competitiveness when applied broadly in a business.
At this point optimization analytics is in a dual mode. On the one hand, there are proven examples of the narrow application of optimization such as those mentioned above. On the other, bringing optimization analytics to the masses is only beginning. Some vendors have made progress in simplifying their analytics, but mainstream products are only on the horizon. It’s also important to recognize that, as with past breakthroughs in information technology, there are bound to be more duds than success stories in initial attempts at using optimization analytics. Experience suggests that a small number of companies that have strong analytical skills and a rigorous approach to managing company data will prove to be the leaders in finding profitable opportunities for applying optimization technologies and techniques. Others will do well to find these examples and consider how to apply them to their own organizations.
Robert Kugel – SVP Research
May 8, 2015 in Business Analytics, Business Collaboration, Business Performance Management (BPM), Cloud Computing, Customer Performance Management (CPM), Financial Performance Management (FPM), Human Capital, Social Media | Tags: Accounting, UX | by Ventana Research | Leave a comment
Recently, Infor held its second innovation conference with industry analysts at its New York City headquarters. Infor’s products include the major categories of ERP, human capital management and financial performance management applications. Behind the marketing aspects of its use of “innovation” is a business strategy for retaining existing customers, migrating a sizable percentage of those customers to the cloud and gaining new customers. (Because of the relative size of the installed base, renewals and migrating customers to the cloud are likely to be more important to Infor’s future revenues than adding new customers.) I think it’s useful to assess the content of the event in the context of the company’s business strategy.
To echo what I wrote last year, the company’s aim is to accelerate revenue growth by offering companies a lower and more predictable cost of ownership than its rivals in the business software market as well as innovation that improves productivity and organizational effectiveness. Infor is trying to innovate by focusing on improving the user experience and lowering its customers’ costs through its software design and architecture. One of the most important aspects of Infor’s approach to innovation is rethinking how users work with its software by simplifying and streamlining user interfaces, adding collaboration–in-context capabilities and providing a modern user experience (UX) akin to what people have grown accustomed to in their personal software. After two decades of development, the bulk of the core features and functions of most business software, especially ERP, have become commodities, which is why UX is increasingly important in vendor selection.
Infor adopted its current strategy because the software markets it serves are mature and offer limited growth using the traditional on-premises, perpetual licensing model. Our benchmark research finds that companies are keeping their ERP systems longer than they did a decade ago – on average 6.4 years vs. 5.1 years. Migrating existing customers to cloud services will enable Infor to increase annual revenues from them. It can charge more than it currently bills for maintenance and still offer existing customers an all-in cost that is at or below their total cost of ownership for the on-premises software. A software-as-a-service (SaaS) approach eliminates the need for customers to operate and maintain the software, and it minimizes the need for third-party consultants and systems integrators to set up, update and modify the application. A significant portion of Infor’s installed base is entities in verticals such as higher education and government that traditionally have underinvested in IT equipment and staff. They are likely to find a SaaS offering an attractive option because of improved performance and even responsiveness to user issues. Infor also will benefit if its SaaS customers buy additional capabilities, adding “edge” application services such as expense management or planning.
Meanwhile, almost everything that Infor – or for that matter any vendor – does to make its software an attractive option for a multitenant environment has the potential to lower the cost of ownership for an on-premises customer. For example, eliminating the need for customization is a prerequisite for any multitenant SaaS offering, but it also reduces the cost of buying and maintaining software that will be deployed on-premises or in a private cloud. Infor’s ION architecture simplifies application and data integration for cloud and on-premises customers.
To achieve superior cost-effectiveness for all customers and make it suitable for use in a multitenant cloud environment, Infor has redesigned its software to be more configurable and reduce the expense of integrating and customizing it. One component of this is building in richer functionality for narrowly segmented micro-verticals so that buyers do not have to pay a consultant to create customizations to provide these necessary capabilities. To lower the total cost of ownership, it has been building multitenant cloud versions of its software (currently there are 33 business-specific offerings) and 15 CloudSuites that automate industry-specific core processes from end to end. Another contributing factor to a lower cost of ownership is Infor’s use of less expensive open source infrastructure and third-party commodity services, which provides savings that can be passed on to the customer.
Innovation in general and a focus on the user experience are essential to the success of Infor’s strategy because they improve the company’s ability to sustain high customer renewal rates and provide a differentiated offering that can enable it to gain market share in adding net new customers. Of course, “user experience” is a bit of a buzz word. When applied to business computing it covers the totality of the effects of an individual’s interactions with the software. Assessing some aspects of the UX are quantifiable (for instance, the number of clicks and screens required to execute a task), while others such as the user’s alertness, attitudes and emotions when using the software are far more subjective and (thus far) usually difficult to quantify. Because the totality of the user experience depends on a variety of elements, many of which are not quantifiable, and – even with the same individual – can vary widely according to context and circumstances, this remains an inherently fuzzy term. Yet, to paraphrase a Supreme Court justice writing of obscenity, we know a good personal user experience when we see it. User experience is not just a pretty face. Data availability, for example, is a constraint that defines the capabilities of any business application. Infor’s ION architecture is designed to facilitate data integration to broaden and deepen the scope of information that its systems can present to individuals as they perform business functions. The user experience in business software involves a more complex set of factors than in smartphone apps; it’s not just the graphic design. Having an information architecture that facilitates collecting and combining all or most of the data to present to a user in a business process can provide a differentiated UX.
To achieve a differentiated user experience, Infor’s Hook & Loop internal design studio has been working for several years to overhaul the design and organization of the screens in Infor’s applications to improve the mental ergonomics of working with business software. Among the more obvious changes have been the reduction of clutter, better graphics and easier navigation. In general, improving the user experience builds on decades of research to better understand how people work with software and therefore how to lay out screens and page flows to make interactions more pleasing and efficient.
Another element of the user experience is how individuals are able to collaborate. Because business is an inherently collaborative process, collaboration capabilities are important to the productivity of business software. Infor’s Ming.le collaboration platform is designed to deliver collaboration in context; that is, the software must be “aware” of what an individual is doing and can provide ready access to the specific colleagues whom the user may need to contact at that moment. This approach is superior to instant messaging and email because the work product is easily incorporated in the discussion. For example, if there is an issue with an invoice, the underlying data about it is viewable and searchable. The discussions around the invoice are saved so that if later some other issue arises about that invoice, the original discussions are readily available to anyone who has permission to see them. That noted, initially Infor may find it difficult to convince finance departments of its utility. In our research only 16 percent of participants said that collaboration features in software will affect performance. This may be because in their initial marketing of collaboration features vendors focused on Twitter-style feeds or a Facebook-style approach that broadcasts widely. As I’ve noted, this style is inappropriate for many parts of a business, especially finance and accounting. However, I expect that as companies use collaboration in context it come to be viewed as an indispensable capability.
The evolution of the user experience is under way, and we believe it will be an increasingly important source of competitive advantage and product differentiation in business applications over the next five years. Smartphones and other mobile devices have opened the eyes of many people to the possibility of being delighted by software, even in accounting and shop floor applications. The next generation of UX will promote the longstanding objective of having software that readily adapts to how individuals work rather than forcing individuals to adapt to the limitations of information technology.
I’ve been covering Infor’s transformation from its inception. The company has made significant progress in creating software that is more efficient to operate, supports better visibility and insight into how a business is performing, is easier to manage and has a lower cost of ownership. It is also setting the bar for improving the business software user experience. That noted, Infor is still a work in progress in a dynamic market with well-financed competitors, and its long-term success will depend on a steady stream of innovations in addressing the requirements of its targeted microverticals, affordability and the user experience.
Current Infor customers should look into whether it makes sense for their company to migrate its existing on-premises applications to the cloud to lower the total cost of ownership or improve software performance. Those considering purchase of ERP, HCM and performance management software should have Infor on their list of vendors to consider.
Robert Kugel – SVP Research