Knowledge in Decision-Making Processes: Driving Dashboards or Actionboards?

On Wednesday, October 28, 2009, I attended the monthly Knowledge Workers Toronto Meetup.  This meetup features great presentations from prominent knowledge workers from the Toronto region.  The event, as usual, was organized by Connie Crosby and Stephanie Barnes.  Regular meetup contributor Martin Cleaver was unable to attend.

The meetup took place at Kramer’s Bar & Grill at Yonge and Davisville.  The use of their upstairs for our meetup is a great way for them to generate additional income on a normally quiet night.  Much to my delight, Kramer’s featured free Wi-Fi for their paying clientele.

Free Wi-Fi, in my opinion, is becoming a must for any establishment serving the modern Knowledge Worker.  A simple request to the bartender provided me with the appropriate router password for my iTouch and a creamy Guinness to lubricate my brain.

Tonight’s presentation was from Ray Gilbert, President of ICTkeynote Inc.  Ray presented his views on how organizations make decisions.  He planned to focus on the evolving need to shift from Dashboards to Actionboards.  This shift proposes the need to present action items as opposed to simply providing status-updates.

My Thoughts Enclosed…Rb

Ray Gilbert presented his insights on reaching beyond reporting.  Like any good presenter, Ray did not present himself as an expert.  There are over 2,000 advisory books released in a given year all claiming expert knowledge.  He knew the crowd in front of him would listen and challenge what they questioned.  Humility goes a long way when interacting with Knowledge Workers.  Ray genuinely engaged with the audience for counter-views and reaffirmation of his points.

To start the presentation, Ray asked the simple question, “what do you do with the data once you have it organized”.  His presentation focused on the means to assist with the decision-making process, using algorithms against such data.

While he has a high regard for quantitative research, Ray concedes that one should not let the data make the decision.  Judgment that can be trusted comes from the context of the content and not the content itself.  There is a need for corporate activity to be directed at reducing uncertainty.

Good decisions must come from collaboration and open discussion on strategy roadmaps with engaged professionals.  Proper Business Intelligence and Analytics comes from “Knowing Your Client” (KYC) ,and applying the appropriate filters and benchmarks.  Only by intersecting data from Providers, End-Users and Business Development, can one bridge the value gap of available data.  Convergence of this content is the hidden gem, that most organizations fail to mine, and tap into.

These diverse conversations provide the general structure to proper decision-making.  So much functional content is available to the enterprise if such silos were dismantled.  To learn you must first listen, and to listen, someone must first speak.  If you can’t hear the pulse of your organization, you cannot learn and see its hidden business values.  You cannot formulate value, if these functional stories are not shared.

Ray Gilbert outlined a three-axis model for making decisions with a scale of Physical->Social, Simple->Complex, and Predictive->Cognitive.  In physical, predictive and simple environments, you can use network collaboration, content filtering, collaboration filters, data mining and fractal analysis.

In a complex cognitive social space however, there is a need for soft tools to assist in the decision-making process.  These tools leverage evidence, expertise, proof, risk, plausibility and possibility. This scale is very useful,  when you reach that point where you need to “guess”.

Ray presented the concept that you cannot fully predict the next wave of business development.  However, he presented ways where you can navigate it effectively with appropriate knowledge.  To achieve this, Ray believes that more human judgment needs to exist in our systems.  By asking critical questions against a mix of soft and hard data, your context drives the decision-making process.

Given that only 60% of decision are made using analytics, the remaining 40% of decisions are simply “gut feel”.  Almost half of the decision being taken are not based on appropriately contextualized content but on intuition.  To address this, Ray presented the three Ps of soft data analytics: Probability, Possibility, and Plausibility.  The decision-making process can be very risky.  The three Ps make the process more adaptive.

Ray Gilbert highlighted the differences between Inquiry and Advocacy-based decisions.  Most decisions these days are Advocacy-based.  People tend to know their answer, and will lobby aggressively to enforce it.

In an Inquiry-based system, you must have a neutral view, and ask questions to the data to find the hidden truths.  Ray related this to  an Accounting Auditor.  Inquiry-based processes make use of collaborative problem solving, testing and evaluation, and critical thinking for decision-making.

Ray outlined that superior decision-making is distressing and difficult to assess.  You need to transform data into insight, to base decisions on these results.  Successful outcomes can be measured against a Right/Wrong and Good/Bad decision map.  The decision philosophy of management is equally measurable using this matrix.  As such, there are lots of psychological traps, that have you at the mercy of your own mind.

Ray Gilbert summarized six key bias traps, that can poorly influence decisions.

  1. The “Anchoring” trap, is when you are already stuck on a data point, and unwilling to see move past it.
  2. The “Status-Quo” trap, is common in cultures that foster a “don’t rock the boat” corporate mindset.
  3. The “Sunk-Cost” trap, occurs when one has paid good money for bad data and the decision makers are unwilling to take the necessary hit.
  4. The “Framing” trap, involves asking the wrong question or asking in a way that drives the desired answer.
  5. The “Confirming Evidence” trap, occurs when you ask for, and only listen to positive answers that validate your views.
  6. The “Estimate and Forecasting” trap, leads to overconfidence, excessive prudence, and selective recall in decision measurement.

Ray used the example of crossing the street to outline the nature of using your immediate environment to facilitate decisions.  Most research takes places in what he refers to as the “Risk Universe”.  You cannot make decisions solely on universe based metrics.  You need the relevant data of your local environment.  Local factors are blended with high level sampling to speculate on the real risk of the decision.

In a corporation, these local factors are often hidden and unavailable due to long-standing Command and Control, and Functional Silos.  It is only through using all three levels of data (Instance, Sample, and Risk Universe), that you can avoid falling into the trap of your “gut” feel.

Ray formulated that judgment is an irrational process. It is subject to biases, moods and time.  It depends on both qualitative(soft) and quantitative(hard) data.  A normal person, stated Ray, can only effectively factor in seven elements due to bounded rationalities.  Ray presented four elements, that are mandatory to an effective decision-making process.

A decision-maker must investigate the “Factors” to be analyzed.  Both the “Evidence” and counter-evidence that is available, must be reviewed.   Unbiased “Logic” needs to be used as a checklist or formula, to ensure we don’t discard relevant data.  Finally, “Risk Tolerance” determines how many rules an estimate requires.  A decision can be made on one good piece of data, only if the factors, evidence, logic, and risk tolerance are applied.

Using the Daams-Stewart algorithm Ray outlined aspects of decydeWARE™.  The Daams-Stewart algorithm outlines the following guidelines for judgment decisions:

  1. Choose Key Factors,
  2. Collect Evidence,
  3. Aggregate Evidence,
  4. Interpret Using Heuristics,
  5. Set Risk Tolerance,
  6. Draw Conclusions,
  7. Make Judgment Call

Ray indicated that one should accept risk if (a) the evidence is strong enough, (b) there is sufficient proof of low risk, and (c) there is little plausibility of high risk.  Fundamentally, if the evidence of your decision is within your risk tolerance, you will likely make the right judgment call.  Sadly, the strength of the evidence is often ignored in that process.  Only by extrapolating using the same rules can we suggest where unacceptable risk is present.  This is very different from just using expectations and deviations in making decisions.  If the deviations are off by your biased judgment, your entire speculation is based on inaccurate facts.

Ray Gilbert concluded the presentation with a discussion on Fuzzy Logic.  By then, the Guinness must have taken hold as my brain also went fuzzy.  All in all, it was a good presentation by Ray.  It required some lateral thinking to assess the value of its content.

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12 thoughts on “Knowledge in Decision-Making Processes: Driving Dashboards or Actionboards?

  1. Hi Robert:

    Thank you for the terrific write-up! I am still thinking about Ray’s presentation, trying to think of questions that might challenge his theories.

    I hope you (and your readers) are able to join us next month.

    Cheers,
    Connie

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