Business Value Analysis
How do you view business value analysis? Buyer? Equity Fund Manager? Seller? Investor? Loan Preparation? CEO? Owner? Broker? Change Maker? There are many views. Each view takes a different business model for understanding business value in their particular situation.
We are more than business intelligence and take a holistic view of the business and it’s environment. Especially for what is your next value initiative or leveraging? The power of Analyzer II version 3.0 gives the user 10,000s different variations of a particular business model whether, maximizing value before the sale, finding the upside of a potential company to buy, preparing to launch a new idea, re-engineering for the loan or exiting plus more. Read an article by Kim that may lead your analysis and reasoning to deeper understanding and a much better way.
Kim Warren
Hypothesis-driven strategy – we can do better.
Experienced consultants have told me how they use a “hypothesis-driven” approach to figure out strategy recommendations for clients.
In summary, this means starting from some well-informed explanation for the outcome of interest. We then seek and analyse data about the elements of that explanation, which may lead to the hypothesis being confirmed, modified or rejected. (Harvard Business School Online.)
Hypothesis-driven strategy is contrasted with either
– a “boil the ocean” approach, where you say “give me all the data”, analyze everything, and see what findings jump out, or
– the use of intuition, trial and error, or exhaustively exploring all options
Thinking back to my recent post on the Pyramid Principle ( ), “boil the ocean” looks like analyzing everything at the bottom and middle of the pyramid – clearly wasteful. Trial and error looks like starting at the left of the pyramid and working across until we bump into an explanation that works (path C).
But there are also problems with the hypothesis-driven approach. In this scenario:
– the data and analysis to test hypothesis A finds it is wrong
– so we turn to hypothesis B, which analysis also shows to be wrong
– so we try hypothesis C, which analysis shows to be correct
So we wasted effort, delays and cost chasing false leads.
And it turns out that hypothesis C is not good enough either, because – as we will see next time – there is a further part of the explanation we didn’t bother looking for because analysis confirmed hypothesis C.
Engineering – not science.
The hypothesis-driven process seems to be driven by a desire to appear ‘scientific’ – we want to explain some phenomenon, for which there are many possible root-causes, and many unknown causal pathways. We can see this in medical research, with the endless studies ‘proving’ statistically that illness A must ultimately be caused by factors X, Y Z. After which, detailed biochemical studies try to fill in the causal pathway by which that happens.
But that’s not our world! We are not dealing with a vast bowl of mysterious spaghetti, but with systems that we ourselves designed. So we are not scientists trying to reveal the mysteries of the cosmos, but engineers, trying to fix and optimise a very well-understood machine. And we already have a robust and reliable theory for how that machine works ()
So … there is a much simpler and more reliable process for strategy-building – whether that is about fixing some challenge or building a stronger future.
The above article leads us to follow an abductive way of reasoning for more solid results and in a much faster way.