Lean Analytics For Greater Speed And Agility
I recently joined SAP; in fact this is my second week. I’m very passionate about analytics, big data and enterprise architecture —and I have been for the last 15 years.
Over the last decade, analytics practices were primarily silos and didn’t have the chance to integrate with enterprises. Since most of the analytics objectives in the enterprises were focused on the “experimental” side of things, very few companies took advantage of “opportunistic” data.
Opportunistic data brings its own challenges, and most of those are in accordance with transactional system comfort. In other words, the transaction system dictates how this data is collected, and most often, the transaction systems aren’t intended to make data collection easier for analytics.
But you know the rest of the story: how data warehousing, data marts, and so on evolved to solve this issue and make it easier to utilize business intelligence and analytics. The point I’m trying to make here is that, however the enterprise system evolved, the enterprise analytics practices haven’t changed in the context of speed. Given the Big Data era we’re in, we need speed and agility in analytical practices and their life cycle more than ever.
Given the volume, velocity, variety, and complexity (3V and 1C) involved, enterprises need to make their analytical practices and life cycle lean. In order to practice lean analytics, they need analytics software and tools that support lean analytics. This diagram is an attempt to capture the value chain of predictive analytics in its simplest, core form.
It’s all about evidence-based decision making. Big Data and analytics have a high correlation with time, so the decisions do also. In an enterprise, being able to make evidence-based decisions at the right time requires near real- or real-time analytics.
Let’s use an athlete analogy; speed is how far you step by quickly stepping. Agility is the ability to sense change, adjust behavior, and take advantage of unexpected opportunities. This is a highly desirable quality. Speed and agility are critical factors in real time analytics. When you combine near real- or real-time analytics with proper analytical practices, you get speed and agility.
The resulting speed and agility in analytics brings enormous business benefits and competitive advantages:
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