“…use analytics to make decisions. I always thought you needed a clear answer before you made a decision…”1 Mitch Lowe, Founder of Netflix
Analytics pioneer Mitch Lowe makes the point: Informed business decisions require an analytics-backed foundation. Our research finds that executives agree: Three out of four companies place digitization, analytics and intelligent automation (DAA) in their top three priorities. One out of four companies consider DAA their number one priority.2 The Internet darlings of the digital age are using data as the fuel of business decision making, with analytics as the engine. But how can you ensure your company is powered by a high-performance engine?
Process analytics is gaining center stage amongst organizations’ decision makers. It is the ability to access data created by process execution, analyze this data in real time and provide insights that are highly relevant for business decisions. This is a step change improvement in performance. In the old days, process management was built around process documentation. Typically, this documentation was developed for a one-off project and poorly maintained afterwards—quickly failing to reflect the reality of how the organization operates. Today, process analytics is addressing this challenge.
While process analytics is not a replacement for more rigorous value chain analysis and complexity analytics, it can be highly effective for certain environments. Specifically processes that are highly repetitive and where process execution is tightly linked to information systems. Leading organizations are creating value for customers in transactional processes. These generate loads of data, but are not bound to any physical assets. This is the perfect environment to run extensive process analytics, get the right insights, and make the right business decisions—the essence for organizations’ long-term survival. A typical case is order management. Numerous data points are created during this highly transactional process, e.g. timestamps, product information and client information. Certain events, like order blocks, can be investigated with process analytics. Trends, patterns and correlations are evident in real time, e.g. certain product-client combinations that cause order blocks. The real root causes are identified and can be eliminated.
Overcoming the data roadblock
Data is key in the digital age; however, most organizations struggle to unlock its potential. The sheer amount of data can be overwhelming. Depending on industry and process types, millions of data points need to be taken into consideration for process analytics. Common tools like spreadsheets fail at this point. But there is hope. The latest process analytics technologies and applications are designed to extract, store and digest enormous sets of data. Moreover, these tools provide functionality for reporting, visualization, pattern recognition, and much more.
State-of-the-art process mining software uses the digital traces of transactional processes to reconstruct what happened in the organization. It shows all process variants, from the most common process flow to a full visualization of all currently running processes. The technology automatically learns how your processes work and detects any hidden insufficiencies in real-time.
However, these highly capable technologies are just one piece of the puzzle. Here is why: The IT landscape for many organizations is often highly fragmented. Relevant data is in multiple sources. Expertise and context from the business and functional units is required to understand where relevant information is stored and how this can be aggregated. Subsequent interpretation of the findings requires business and functional expertise, with a combination of statistical skills and business background increasing the quality of outcomes.
Illuminating the future
The investment in process analytics will pay off. Our experience reveals that companies’ process improvement journeys are significantly more likely to be successful if process analytics is applied. Whereas in the past, interviews, estimates and spot analyses were the means of choice for illuminating issues, today hard facts and real-time data are the primary source of insight. In a global survey, more than 70 percent of respondents believe that the use of data will play a central and embedded role in management and decision-making processes in the next five years.3 Biased inputs and incomplete diagnostics of the organization belong to the past. Quality data is the future.
Moreover, agile methodologies allow for more detailed diagnostics in much less time. Experience shows that project timeline reductions of up to 50 percent are realistic. At the same time, diagnostic outcomes are of much higher quality. Agile methodologies, combined with the right set of leaders from business and IT are the secret sauce for quick, high-quality outcomes.
The combination of process mining software, sensors and other enabling technologies has reached a level of maturity that provides opportunities like never before. Scalable systems allow for analyzing multiple processes simultaneously.
The time is now. Reveal better business insights through analytics-powered process management. Overcome the blind flight!
2 Accenture Digital, Supply Chain Analytics research, 2017
3 Accenture Technology Vision research, 2017