Strategy, Tactic, and Data

During develop a product, we need to intelligently set up a process for idea, execution, or pivoting business model if necessary.

On the other hand, nowadays, data-driven business is a famous topic of many articles and news. Perhaps you recognize it as Big Data, Data Science, Data Insight and so on.

So, is it true that the business process (which automatically also means product development) should be driven by the data?

To answer this, I held understanding that the simplification of the product development process consists of two phases:

  1. Strategic
  2. Tactical

At the strategic phase, we tried to make the concept, stringing understanding of holistic/comprehensive view, and this is a basic foundation for the next phase (tactical phase). This phase is often used when we initialize a business, a product, a service, or a new feature. At this stage we must open wide the doors of all the possibilities and opportunities with Opportunity Mindset.

In this phase, do we need a data-driven analysis to make a strategic decision? Rather than data-driven analysis, I prefer to call it a “flash of information/knowledge/experience”. Malcolm Gladwell called it a “thin-slicing” in his book Blink. Somehow, the bulk of information, knowledge, experience, and “gut feeling” is so systematic and automatic. It is a main roadmap that will be detailed into tactical executions. What we need is reinforcement of an idea. Even for an idea that really new, the need for supporting data is so minimal or even not needed at all, as well as Steve Jobs had done when he launched Apple Macintosh. Too early data-driven analysis, making the data submitted to multiple interpretations and the result is biased.

Well, as you might have guessed, the data-driven to be so crucial when entering the tactical phase. At this stage, we begin to enter the technical area, detailing, pragmatic (adjust people, cost, timeline). But it does not mean we do Constrain Mindset.

We need to adjust our expectations into reality. Adjustments to context and or to the next context which will be formed later. Start from customer feedback, market landscape changing and so on. And the most important thing is our interaction with business partners and customers. So, data will be automatically generated. This is our gold mining to do analytical processing.

Not only in order to improve our existing product, analytical processing will open up opportunities for new product/service. Analytical processing also will contribute to add a layer of information/knowledge/experience to the next strategic phase.

Roman Pichler puts strategic phase while developing product roadmap, and puts tactical phase when detailing product backlog:

If you familiar with The Lean Startup Process — Diagram:

And you can distinguish between Goal vs. Objective:

Then our discussion above will look like this:

Furthermore, if you are familiar with some of the best practices in software development such as: Design Sprint, Agile Methodology, Continuous Delivery, Product Research: Business Development + (UX) Design Research, Data Engineering and Continuous Improvement, the chart above will be cover image in this article:


I’m a product-market fit builder | ex-Samsung R&D Institute Indonesia | | ex-Tokopedia