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Reticent = Reluctant: (Un)willingness to embrace New Data Paradigms

Maintaining the status quo or driving change now?

25Jan

reticent

[ret-uh-suhnt]

1.

disposed to be silent or not to speak freely; reserved.

2.

reluctant or restrained.

Obviously, there might be even too much information about Big Data/Analytics, cognitive computing, machine learning and new-era data management in general – I am sure you have noticed.

Companies like GE, Rolls-Royce, Coca-Cola or Unilever are at the forefront of innovation in this area – rightly so – they have a huge brand, tradition, resources, best practices and perhaps culture based on confidence, collaboration, being established, already a pioneer - dedicated to either sustain that status or in better cases, innovate and disrupt even more.

Still, there is myriad or companies and organizations, who are on the other side of innovation continuum, so to say: current state of technology being sufficient (or at least perceived that way), some of the leaders being called Old School, not willing to Rock the Boat, etc. You know what I am getting at. All this is understandable though and fair enough.

Janaki Kumar, Head of Strategic Design Services, SAP, provided great insights in his Forbes article:

If a company is reticent to make change, start empathizing with people who are skeptical. That can mean doing things in the way that is expected at first, then undertaking additional work to present an alternative, creative solution. Share the results of both efforts, creating an opportunity to witness the benefits of a design thinking approach. 'Senior management starts paying attention to stuff they don’t understand that’s successful, because they view themselves as having their arms around the whole thing.'(http://www.forbes.com/sites/sap/2015/11/17/how-to-find-innovation-in-unexpected-places).

In Analytics/Data management context – despite having cleary articulated strategy (and resources) in this area, it might be worthwhile starting the discussion, understand current company environment around tools, people, processes and culture and even without world-changing ambitions, start small and try to embark on an Analytics Journey – either via a departmental PoC (proof of concept), on a smaller dataset, to establish credibility with Doubting Thomases to start with – if done right, the rest will follow – my friends at Keboola have something to say on this topic – especially if you want to tidy up your company data sources, fast and need user-friendly insights.

Or even before that, or concurrently, get your head around the wholeAnalytics/Data Management space and seek practical, innovative options for your business – there are companies who can provide a so-called Big Data/Analytics: 1-Day Immersion Programme, workshops aimed at providing fundamental insights, before you take action of any kind.

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