ManMachine – The Computer Human Synergy for Organizations

TARGIT CEO, @MortonSandlykke has a very topical post today, ‘Turning Emotion-based Decisions into Fact-based Decisions’.

Morton’s basic premise is that while information availability might have been a bottleneck for better decision-making in the past, that is not the case today.

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(c) SmiEyeTracking Flickr

Today the human is the bottleneck in the decision-making process.

We have been programmed to act on our own biases – built over time through our experiences and our learning paradigms; and colored by our own contexts, cultures and objectives. So, now when we are at the other end of the spectrum – drowning in information – our instincts kick in and we resort to ‘gut-reaction’ decision-making.

Business Intelligence is worth nothing if you don’t change your behavior……..Instead of letting the computer drown you in data, trust it to lead you to a conclusion.

Most of us recognize this truism and may truly believe that we are, in fact, making data-based (or, evidence-based) decisions. This is true in some cases at an individual level but extremely rare at an organizational level. Organizations are still largely structured for gut-based ‘leadership’ and ‘executive’ decisions. There is very little scope for learning from patterns in the data or for running experiments to choose the best strategy.

Q: Why can’t organizations step up to fact-based decision-making?

A: Because they cannot describe the organizational decision-making process.

While most organizations have systematically described their processes, structures and data-stores, the decision making is still in the managers’ heads. Good managers make good decisions and if there are no managers, decisions don’t get made. This is a serious handicap in being scalable and being consistent in business.

Decision modeling using the new DMN Standard and the DecisionsFirst tool are good starting points to start describing decisions.

For Man to truly trust the Machine the decision-making responsibilities between the two have to be explicitly described first and judiciously partitioned next.


8 comments for “ManMachine – The Computer Human Synergy for Organizations

  1. Gagan
    April 22, 2014 at 9:52 pm

    You make a great point about decision-making capacity needing to be a first class citizen of management models.

    This has not received the attention it deserves because the ‘knowledge’ required to make decisions could not be abstracted (extracted?) effectively. Today knowledge representation technologies like business rules management systems, analytical models and optimization algorithms are becoming mainstream and there are mechanisms like the DMN standard to to represent decision models. All these make decision management much more accessible and useful for general management.

  2. April 23, 2014 at 5:38 am


    Your comment concerning the “technology of modeling” is timely — it is both easier to model now and business modeling is better understood.

    That said, we are also seeing the phenomenon in the world of big data where data is apparently supposed to be “self-modeling”, i.e. you don’t need to model because AI-driven analytics will figure everything out for you. OK, this is an extreme characterization, but not unfair. And the temptation to the “modeling free lunch” has deep roots.

    Part of the governance challenge here is that modeling is a cost-centre-based activity. Before I moved to the world of sales, I was a B2B market research analyst for IDC and DEC. The tools weren’t nearly as powerful then (to the early 90’s) as now. One of the governance lessons I learned was that organizations only support cost centres grudgingly.

    Such understandable cost-aversion explains the challenges that are faced by any of a varied number of careers, including enterprise architect, business analyst and maintenance technician. If you can turn your cost-centre into a KPI-driving enterprise leverage point, you’ll be a lot better off.

    Here is a blog post I wrote last year on the importance of modeling in a big data world:

    Is modeling useful? Certainly. And are there powerful modeling tools available? Absolutely. But do we have the same challenges for making them useful for the organization. Yes. But it can be done!

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