Three Big WHEREs to use Big Data

By deploying Big Data’s WHY, WHAT, HOW, WHO, consequently we come to discover Big WHEREs need Big Data insight:

1.   Decision Point

Both academic and industry research suggest that companies use data and business analytics to guide decision making are more productive and experience higher ROE -returns on equity than competitors that don’t.

• Big Debate: There are many interesting debates to brainstorm Big Data potential to influence decision making:

1)      Does big data complicate decision or drive the right decision?

2)      How to filer out the noise of big data in order to make sound analysis?

3)      Big Data is about those small tweaks and chat, can it help solve big business problem?

• Big Judgment: That is said:  Big Data need big judgment. “. Big data and big analytics will dramatically amplify the effects of human decisions, which is great if those decisions are timely, sound, and effective—but potentially catastrophic if not.

• Big IQ (Insight IQ):  Some organizations build an “Insight IQ” index to measure the analytic maturity of employees: such as ability to find and analyze relevant information to make better decisions. The three elements of Insight IQ are information attainability, information usefulness, and employee capability

2.   Customer Touch Point

• Behavior & Sentimental Analysis: Customer-centric businesses have already used data to segment and target customers. But Big data leapfrogs such analysis to the state of the art by making real-time tailored customer solution possible via tracking the behavior of individual customer, update their profile, and model their likely behavior in real time, such in-depth customized analytics or sentiment analysis will increase the chance for high value customers to purchase higher-margin products or service , also help adjust business/marketing strategies accordingly. 

• Insight from Call center: some call center providers are embracing new analytic tools to dig deeper into the big data they generate. Companies are applying text and sentiment analysis to the unstructured data, and looking for patterns and trends,  to analyze agent records, identify customer concerns, highlight trends and patterns, and provides early warning capabilities. Call center logs can provide invaluable insight on what customers were calling about, and can also provide foresights for future product trends and what customers need for the next.

      3. Process Optimization Point

Like business analysis, the rise of BPM reflects a growing view that processes are instrumental in driving sustainable competitive differentiation. Distinctive business processes make one company stand out from its competitors. Differentiated and effective processes can create speed. Efficiency and agility to help organizations better adapt to the dynamics of the business environment

The alignment of BPM and Big Data Analysis can be seen from following perspectives:

• Injecting analysis into business processes to improve decision-making – i.e. it helps take well blended,  inside-out process view and outside-in Big data vision in decision making process.
• Closed loop feedback management—via big data analytics by digging into customers feedback & suggestions, business may practice closed loop feedback management discipline and optimize end to end business process to further delight customers or engage employees.

  There might be many BIG WHEREs need Big Data insight, via exploring such big three WHEREs, the business can walk the talk, to reach the destination step by step