• September 28, 2016

Data Gone Wild: Rein It in With Always-On Analytics

With business process optimization, you can weather the Big Data tsunami.

The digital environment is exerting enormous pressures on the enterprise to maximize speed, accuracy, and predictive capabilities. This requires the savvy exploitation and application of Big Data. But consider this: Every minute, YouTube users upload 300 hours of video, Facebook users like 4,166,667 posts, and Pinterest users pin 9,722 images. And that’s just a snippet of the data generated from social media alone.

No enterprise can thrive in this digital data tsunami without developing strategies to rapidly capture, analyze, and apply vast and divergent reams of information. Yet with blazing processor speeds and robust predictive tools, this paradigm-shifting challenge is achievable. It starts with embedding always-on analytics into business processes such as marketing and sales, purchasing, customer service, and compliance. When an enterprise executes these analytics-enabled process strategies with an eye on clearly defined outcomes, leaders can make smarter decisions faster. And those decisions will likely generate greater business value.

Moving From Slow to Warp Speed

It wasn’t long ago that companies extracted data from transactional systems and then off-loaded it to another system for crunching. This process could take anywhere from hours to weeks. Each response to the shifting marketplace required multiple steps, costing enterprises dearly in resources and performance. Even worse: Once the enterprise adapted and changes were in place, the market often shifted yet again.

But by integrating data analytics into key business processes, enterprises can monitor decisions, assess performance, and course-correct—often on the fly. That’s crucial because now more than ever, organizations must respond quickly to customer demands by executing faster while keeping operational processes flexible. Always-on analytics equip the enterprise with rapid response capabilities to tackle changes in supply, demand, product design, and capacity. This can drive down costs, drive efficiencies, and boost profitability.

How can enterprises implement process-optimization strategies? Start by developing an accurate view of how the actual business process is executed. How do users interact with the applications and data that form the process from end to end? How does data flow through the process? How is process-related data captured, and where is it stored? Does it reside in different systems? Is it siloed? What does the data reveal? What does it leave in the dark?

Armed with this information, enterprise leaders can begin to tackle some fundamental questions. What is actually occurring? Why is this happening? What is likely to transpire in the future? How should we strategize to meet that future? By leveraging predictive analytics and performance management technologies, the enterprise can quickly grasp what is happening and devise strategies to improve these processes.

Beware of Siloed Cultures

Too many analytics teams, businesses, and IT professionals work in silos. They operate with different processes, speak different languages, often have clashing priorities, and hold varying understandings of business problems and the associated analytics. That’s why it’s critical to build teams of IT developers and analytics specialists to work together closely throughout the process. Sprinkle these teams with specialists who clearly understand the IT systems, analytics processes, and business problems.

With always-on process analytics, the enterprise can uncover unexpected patterns and develop models 
to predict likely outcomes. The results can generate heightened process performance and deeper insights, taking the enterprise to the next level.

Like this story? Learn more about accelerating better business outcomes with analytics.