DATA-DRIVEN DECISION-MAKING – HIPPOS & DAPPOS
“All the talk about data driven decision making and its value in de-risking business strategy has always made me think about the whole concept of business intelligence.” — Sameer Rahman, CEO DataMonet
Having experienced decision-making in various organisations, my take on data-driven decision-making is different…
I think the difference between experience-based (gut feel) decisions and data-driven decisions is not as stark as it is made to believe. When a CEO of a company makes a business decision based on past experience and gut feel, it is still based on data points.
Data that lies in their head, data that they have been exposed to before, data that they have gathered over the years, data that has been tested for success / failure in the past, and data that can be put into the context of current business conditions. They have just made decisions on these virtual datasets in their head.
So, these so-called gut feel decisions are not that devoid of data as it has been portrayed, as it is these virtual data points which culminate into experience-based decision-making. The HiPPO (Highest Paid Person’s opinion) is not that data agnostic in my view. After all, there is a reason they are HiPPOs, as they have gathered and used data points to good avail in the past.
The little secrets of decision making…
But while I think the fundamentals and principles of gut feel and data-driven decisions are still the same (both based on data points collected), the way we collect, analyse, interpret and use this data is what makes it different. It is almost impossible to connect all the dots with data points in your head and work out the right methodology to produce the insight to get to the right decision. This is where the analysts of the modern age come in and work their magic (or logic).
So, I think the world is not as divided as it sounds. But for data-driven decision-making to be most effective, it needs to be a collaborative approach between HiPPO and, let’s call it, the DAPPO (Data Analyst Paid Person’s Opinion) approach.
1. Data collection
- HiPPO: Gives their views on which data is important from past experience
- DAPPO: Decides the data collection plan, what data to collect, how best to collect this data and all the technicalities around data access, quality, etc.
- Risks: Ensure a balanced view is taken and that the HiPPO’s recommendation on type of data is not based on too much bias
2. Data analysis
- HiPPO: To share their experience (not opinions) from the past on trends and form a hypothesis
- DAPPO: Looking for patterns and trends and visualise the data to see if the HiPPO’s hypothesis on which data to focus on is right. If it is, then focus on this dataset of maximum value to connect the dots rather than getting lost in the sea of data. Form their own hypothesis and test it with data
- Risks: Again, not led too much by HiPPO’s bias and past experience
3. Producing Insights
- HiPPO: Sit back and relax
- DAPPO: To connect the dots, affirm or negate the HiPPO’s hypothesis. Come up with their own version of truth and clearly highlight the evidence with tangible actions (focusing on ‘So What…’)
- Risks: Make sure evidence is strong and significant to negate HiPPO’s hypothesis
4. Taking Actions
- HiPPO: Due to their seniority, HiPPOs are best placed to absorb this insight and decide on the best and most commercially rewarding action to take (not forgetting their focus on the consumer)
- DAPPO: Take note of the actions suggested by HiPPOs for your own learning
- Risks: DAPPOs need to ensure their insight is not misinterpreted in any way and the actions are truly reflective of the insights produced
Conclusion
A truly data-driven organisation is where experience and data work together to produce evidence-based insight resulting in experience-based decision-making.
Speed Read:
- Consider experience and gut feel as a collection of data points.
- DAPPO working their logic with data and HiPPO working their magic with decision-making is the most rewarding combination.
- A data-driven organisation is not just about the power of analysts and data but the strength of collaboration between HiPPO and DAPPO.
I will probably earn some brownie points with HiPPOs and a backlash from DAPPOs with this article.