The Dark Side of Digital Transformation

Digital transformation is failing, a new age of business intelligence is dawning — This week's post comes from Holistics team member Yahya Apristianto, who wrote it after attending a talk on digital transformation by a CEO in his home base of Indonesia. In this piece, Yahya opens by citing McKinsey's surprising statistic that 70% of companies fail to successfully complete large-scale digital transformation programs.

He then extrapolates from this to the observation that business intelligence is particularly affected by failed digital transformation efforts. Historically, BI has been one of the first functions of a business to get digitized. This means that any old organization that wants to do a digital transformation project has probably already done so ... in the BI department.

This is particularly interesting to us because we're beginning to see a new wave of approaches in BI, championed by tools that take advantage of the common availability of cloud software and the power of new data warehouses (old topics that we've covered many times here on Holistics). What would digital transformation mean when it's a second wave ... given that so many attempts at a first wave have failed? We'll have to wait and see.

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Links From Elsewhere

The Perils of Constant Feedback — Tom C has a hugely entertaining post that's informed by feedback mechanisms in machine learning. This isn't strictly business intelligence, but anyone who has worked on or owned work projects would probably resonate with Tom's core query: how much feedback is too much feedback? And how much time should you spend working alone, driven by a vision of the end result?

The answer isn't very surprising: you don't want too much feedback, and you don't want too little. The way Tom gets there is highly enjoyable, however, and comes with a little detour into learning algorithms (and lots of animations).

Why You Need A Career Ladder (a series in three parts) — Caitlin Moorman over at the Locally Optimistic blog talks about creating a career ladder for yourself — a roadmap for the next few years in your work life. The post is split into three parts (with sequels here: two, three); the first part is written for the general case, and not necessarily for those of us in data. But stick around — the latter parts present sample career roadmaps for data teams. Highly recommended.

That's it for this issue of Inner Join — see you next Wednesday!

Warmly,

Huy

Co-founder, Holistics