Tuesday, January 13, 2015

Digital Master Tuning XI: How to build a Digital-Intelligent Organization

Data analytics is an ongoing capability, not a one time project.

Digital is the age of Big Data. in high mature, digital intelligent organizations (Digital Masters), Data analytics is not a one time IT project, but an ongoing digital capabilities. In the book of “Digital Master,” we introduced 12 types of digital intelligence to guide organizations through the digitalization journey systematically. And organizations shall continue doing self-checking: What’re your Big Data objectives? How would you meet them? Is it just by having a clear vision and set of objectives? Is it adopting a business-driven process? Would the tools or skills play an important role? Shall you build an analytic CoE (Center of Excellence), and how about your analytics talent potential?

The purpose of doing big data analysis at all is to produce proactive foresight and actionable insights. These insights are evaluated by several criteria: degree of surprise, relevance to business activities and goals, customer insight (“know what they need even before they know themselves), effectiveness at guiding business actions, reproducibility/reliability of the insights, and opportunity to extend the insights into other business areas. Insight provided by Big Data is always in the context of the questions asked by the business. You need to ask whether a 'successful' implementation actually creates returns to the business. This starts to blur the lines between whether a business is capable of implementing the changes necessary that the actionable data has given them. It means they'd understand the insight and be able to address it if ROI justifies the cost. The effort to implement could be simple reporting to major changes in business processes or even a change to corporate goals (which has many other implications) which means the company needs to be sufficiently agile to address this.

There is a maturity curve there for big data. The big time benefits from Big Data goes to the solution that is best at understanding unstructured data. By reviewing social/mobile content, etc. if you can parse this content to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information you can gain competitive advantages over rival organizations and other business benefits. Structured data (internal or external) will always be used in conjunction with the unstructured data.You can’t draw the full path right from the beginning. Big data activities inside an organization has to prove its value first and this happens by early adopters (evangelists and skilled resources) and an executive support. If you start from scratch and omitted this first exploratory phase you will either focus on technology rather than the use cases or start with overwhelming use cases that the business can not absorb. This pattern happens in many successful cases, and missing in each failed story. What makes for a successful implementation is laser-focused, non-ambiguous action items. The more modern-day approach is that analytics MUST be actionable for success. How you get to the step where the C-level executive knows exactly what must be DONE is the art of data analytics.

A successful BI/BDA implementation should be measured on multiple scales. There are still organizations that keep to do a traditional KPI-driven analytics approach. KPIs are most common, thus they get used "by default". But what does it take so that you can identify more practical "action items"? A multi-scale measurement includes:
1) Management perspective. Was the system implemented successfully? Were all necessary data sources integrated?
2) New insights. Were new insights presented or able to be derived that would not otherwise have been possible?
3) ROI. The process of setting up a BDA system will need all common project aspects from sponsorship to implementation so carries an internal cost of setting up as well as any additional IT spend. Do the results of the system outweigh the investment in the system and its ongoing maintenance? Other measures then become more of a measure of the maturity of the company as to whether the actions given by the data insights can be implemented successfully, not the BDA/BI system itself.

Data analytics is a journey, you need to follow the principles, tunw the process, unleash your talent potentials, and build it as the embedded digital capability to compete for the future.
Try this Digital Master Fun quiz

9. The high mature digital intelligence is decoded as a “type’ of card, which type is it:     
A: Unique  B: Wise  C: Special  D: Smart


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