Mark Smith's Analyst Perspectives

Predictive analytics has the potential to help businesses increase the impacts of their actions by creating indicators that represent future outcomes based on existing behavior. This process becomes more complicated when they have to apply predictive analytics to what we call big data environments. As yet only 13 percent of organizations are using predictive analytics according to our business analytics benchmark research, although 37 percent indicated that predictive capabilities are very important to their business analytics efforts. Opera Solutions is one of the larger vendors of dedicated predictive analytics software, having more than 650 employees, more than 200 of them data scientists, who help organizations turn their data into actionable intelligence. There is opportunity for the company, as predictive analytics and visualization of data are two capabilities not available in four out of every five organizations according to our big-data benchmark research. Beyond creating indicators, Opera Solutions’ applications can generate signals that present results not only visually but also in English sentences that integrate the analytics and provide guidance for determining next steps. This sophisticated capability can help improve business processes and refine decision-making and truly interact with the application.

Its technology platform Vektor processes large volumes of data and uses advanced analytics to create a Signal Hub in which users can visualize past, present and future performance and also create indicators in English using models that apply computational algorithms and mathematics. The results can generate specific recommendations within the context of the user’s business processes, much like expert systems did in the past. By processing data through rules, logic and analytics, Opera has achieved faster growth than other vendors of predictive analytic tools. More than half (58%) of organizations today want to deploy predictive analytics with business applications for real-time execution, according to our predictive analytics benchmark research. Opera Solutions enables this through a data discovery process that uses workflow, rules and logic across as many analytics models as necessary.

The company’s management realizes that its software must interoperate with others in the market. As a step in this direction, at SAP’s annual user group conference SAPPHIRE NOW, Opera Solutions announced a partnership to utilize the compute power of SAP HANA, the in-memory computing database technology. Opera Solutions processes some of the largest stores of big data, including for customers and transactions, which are critical to more than 60 percent of organizations according to our big-data benchmark research. An important feature is that it retains the lowest level of transaction data to provide any details required to understand a situation and guide action. In-memory databases like SAP HANA will have high growth rates in the next two years in big-data environments. By integrating with it, Opera Solutions is ensuring that it can process and compute increasingly large volumes of data that its existing database and processing technology won’t be able to handle.

The company’s largest challenge is to communicate the power and sophistication of its platform to customers and differentiate its approach from other predictive analytics vendors. SAP markets its own set of predictive analytics tools that operate against HANA, but to use those requires skills and resources from customers, and the lack of these is the largest inhibitor to organizations using predictive analytics. Thus the two companies take starkly different approaches, and Opera needs to emphasize that further.

Opera Solutions can help organizations realize the benefits of a business investment in predictive analytics. Our research shows that first in importance among them for more than two-thirds of organizations is achieving a competitive advantage, and more than half each want to identify new revenue opportunities and increase profitability, as well as increase customer service. Opera Solutions also offers preassembled capabilities for specific industries including for consumer-focused finance and risk management, global financial marketing, healthcare, government, marketing and the supply chain. I had a chance to review its supply chain intelligence and financial wealth management applications; they present what is going on within a business context, not just in charts but in actionable explanations in English, which are much needed in organizations using dashboards that provide no insight on what should be done next. Opera Solutions addresses the need for focused business context but also increased usability – the most important technology and vendor consideration in 70 percent of organizations evaluating purchases. The applications also are configured to provide usability for specific roles, from executives to managers to analysts.

Organizations that have expert resources on staff, such as data scientists, get the most value from and are the most satisfied with their predictive analytics. But today 83 percent do not have sufficient skills or training, and more than half (58%) do not understand the mathematics to properly apply predictive analytics; these are the largest obstacles to using the technology in more than three-quarters of organizations.

Opera Solutions offers help for these organizations through its own experts who create applications that non specialists can use from executives to managers and management. The tools enable business analysts to get down to actual analysis and develop recommendations for action; our business analytics benchmark research finds this to be a critical need, as two-thirds of the time analysts spend in the analytic process goes to data-related tasks.

Opera Solutions takes care of the heavy lifting, from data processing to the hosting of the platform and applications that organizations access. But it must make it clear that this is not outsourcing of analytics but augmenting the customer organization’s capabilities with applications and support from a team of scientists. This combination of tools and service can help organizations focus on analytic outcomes and advance their business goals. I would also like to see advancements in utilizing collaborative capabilities to help create a decision making network in the business that can encapsulate the issues and resolutions for tracking towards an organizations goals and objectives. As Opera acquires more customers it will need to improve automation of the movement and preprocessing of data, which the company currently does manually with its own tools. Its browser-based access, even from a mobile tablet, allows management as well as analysts to review and act on analytics in a more expedient manner. The dynamically created and readable signals Opera provides are a significant technology advance that very few others can approach. Personally this approach is one of my favorite methods because it gets past just delivering charts in a dashboard that have no explanation or guidance.

Since this approach is unique and sophisticated, it will require Opera Solutions to explain how it delivers faster time to intelligence than other suppliers of big data and predictive analytics. It has to communicate that it is not out to sell a predictive analytics tool that requires an organization to acquire the skills to use it but instead wants to work with the organization to present analytics and signals in an easy-to-use application. The challenge is that at this point the market is not educated on the science of analytics and the value in what Opera Solutions is offering. If you want to increase your competence in applying analytics against your big data and gain intelligent signals that explain your current situation and implications for the future, look at how Opera Solutions is changing the face of predictive analytics.

Regards,

Mark Smith