XII. Decision-to-be-Made

The sharpest tool in your business-understanding inventory
Dr. Albert Künstler

hen put in front of the supreme lord before starting your Quest journey, nothing will be more valuable to gain from your brief audience, than the statement of Decision-to-be-Made, explained by the high lord in his own words.

Tool: Decision-to-be-Made

Best for: Interviewing the highest-level sponsor

Required time: 15–45 minutes

Main result: Challenge-Question clarified - What exactly do we need to solve?

Secondary result: Criteria-Question unfolded - How do we know that our solution is good?

Decision to be Made — the sharpest tool in your business-understanding inventory.

Some inexperienced heroes choke in the face of the great lord, while others begin to verbosely praise themselves, advertising their past merits. This is an unwise use of precious time. Instead, you will impress the quest givers by immersing yourself in their problem skillfully and decisively.

Your research is sponsored for a reason. The quest giver who generously commits the funds to your team will await your return with the gems of knowledge or an ingenious algorithm that will guide desired business decisions. Thus, a wise hero shall start with understanding the purpose, the desired decision.

10-minute guide

ecision — what kind of answer is required exactly, what is the question in hand, and what are the alternatives to choose from, what data is available or shall be collected?

ime — when should this decision be made, how often do such situations arise, and how much time is available to find a solution?

arriers —why is the choice hard to make? What makes the old way the wrong way, and why is the quest giver employing you to invent a new method?

etrics — how can you distinguish a good decision from a bad decision, what metrics are the most important, how does the business benefit from more accurate decisions?

30-minute guide

Once you have more time with the sponsor, it’s always commendable to dive into a deeper level of understanding and uncover the decision making logic.

Decision-to-be-Made: High-level Decision Logic diagram.


  • Discuss what alternatives are being considered.
  • Are all alternatives known? Do they want you to explore, find, and develop more options?
  • What data is usually available for making similar decisions? Do you need to search for additional sources?
  • When data is at hand, what factors or signals are usually more important for choosing between alternatives?
  • Try to visualize the decision-making logic. Is it a one-step or multi-step process and are there any intermediate choices and decisions?


  • What kind of process is it? Is it a once in a lifetime decision, e.g. a unique discovery or a strategic move by a sponsor, or is it a recurringprocess worthy of a solid decision-making algorithm. If the former, what business events constrain the time available for exploration, and if the latter, what conditions constrain the time available for computation?
  • What business events trigger the decision and how often they occur?
  • In such situations how frequently each option has been chosen over the alternatives once the decision is taken?
  • Which steps of the current decision-making process consume most of the time and why?


  • Which steps of the current decision-making process must be fueled with more data or require improvement or reengineering (e.g. improve accuracy or reduce delays)?
  • What are the main reasons for the mistakes and inaccurate decisions? Is it possible to locate those blockers and barriers in the process?
  • What are the main reasons for the delays in the process?
  • Which resulting options are most sensitive to mistakes from the business standpoint?


  • Is it possible to evaluate the accuracy of this decision? If yes, how can it be measured?
  • What is the desired level of accuracy? Is there a reason to believe this level to be achievable, or is it just a fancy number, e.g. 90%, 95%, or 99%?
  • Is it possible to quantify the cost of inaccuracies and mistakes for the most sensitive cases? Can we quantify the impact: does a 1% improvement in accuracy generate or save X amount of money for the business?

45-minute guide

In case you have the luxury of 45 minutes of the sponsor’s undivided attention, you may dig even deeper. This is a rare situation, as usually senior sponsors drop off from the conversation after 20–30 minutes or earlier, so this level of deep-dive may be held with the second-highest person on the quest giver’s behalf.

Here is what you may discuss to get the complete picture of the decision-making process.

Decision-to-be-Made: Detailed Decision Logic diagram.


  • What are the preferred decision-making patterns: choice by eliminating inappropriate options by a sequence of factors or weighted balanced scoring of multiple factors?
  • Are we expected to pick one option out of several alternatives or suggest a short-list of several options?
  • How do we make a decision when a significant factor is not supplied with data? Do we make an assumption? What is the rule?


  • Based on previous experience, how often in the process is each branch of the decision tree employed? The exact numbers are not required at this point, but a rough evaluation may give a good understanding of the decision-process mainstream paths.
  • What happens if the decision was not made on time? Is it more harmful to the business to make a wrong decision or make no decision? What is the cost of delay?


  • Is it possible to specify the reasons for mistakes or delays in the process?
  • Data issues: incomplete information, poor data quality, slow data collection process, noise, bias, high variability, and a lot of edge cases.
  • Operational issues: delayed or restricted access to data, imperfect tools, human factor, not enough people, motivation, or training?
  • Put these reasons on the diagram.


  • How do we measure overall accuracy? Are some kinds of mistakes more critical for business than others? Do we have a more meaningful metric rather than a percentage of wrong decisions?
  • How can we compare good/bad options for non-binary (yes/no) choices? Is there a formal way to evaluate these options? What is the principle to measure accuracy and compare complex resulting output, e.g. ideas or pieces of advice?
  • What is the current (as-is) accuracy and how far are we from the desired accuracy (to-be)? Has anyone (competitors, peers) achieved that level of accuracy? Do we have an idea how much the cost of that transition has been?

We now have a detailed DTBM — so what?

Let us remind ourselves, we are on the “Question” phase of our QUEST. And our current need is to clarify Challenge and Criteria Questions and collect enough information to transform a sponsor’s business problem into a research problem for our team of explorers.

Having DTBM decomposition we now see the business problem in all its splendor, with the inputs, outputs, and outcomes, together with the steps, barriers, event flows, and costs. Such a view is extremely beneficial for finding a solution. In order to find a solution to the original business problem, we now see the set of smaller subproblems and can prioritize and target them. Though we can not solve all these problems at once, we can now see the blockers, evaluate the impact of those barriers, do our research, and eventually offer a set of Solutions to the Highest-Impact Problems.

Here are some research activities that your research team can do with a clear view of why they do it and how it is valuable for the business:

  • Collect more data to improve the accuracy of the decisions;
  • Find and explore new ideas to increase the number of options;
  • Develop better decision algorithms to reduce the number of mistakes;
  • Reengineer the decision logic to reduce delays, human errors, and associated costs;
  • Build predictive models to reduce uncertainty and fuel more accurate decisions;
  • Cleanse and filter the data to improve signal/noise ratio and reduce inaccuracies;
  • Explain data and unknown phenomena so that the previously unrecognized signals acquire meaning and drive better decisions.

The above listed activities are quite standard in the world of researchers — all you have to do is to connect them through DTBM to the business problems that come from the world of business.


So we took advantage of the high lord’s attention and worked out the details of the business decision that our Quest would serve. We found out the main purpose of our research — the “Decision-to-be-Made”. We mapped out the decision logic, identified the available sources of data and the reasons for possible difficulties, and also got an idea of ​​how to evaluate the quality of the resulting options.

However, not all questions are clear to us just yet. What are the deadlines and budgetary constraints of our Quest, who are the key people, how do the outputs and outcomes fit into the strategy? We need answers to these and other questions that are required for a successful mission. To clarify these details, it is no longer necessary to seek an audience with the highest boss. Someone of a lower rank will be perfect for the discussion, but this discussion is just as important, for which we apply our second tool, the MISSION Canvas, that is to be discussed in the next chapter.