Complex Questions & Tools

We just came out of a full day session thinking about fostering collaboration within the office environment. Overall an interesting day, albeit it a big unspecific for my taste. About midway through the day, I sat and listened to a conversation between two colleagues who were discussing the challenges that both of their teams face with helping answer questions from the field.

One colleague commented how on their team the nature of the questions were generally much more transactional without a lot of opportunity to interact and dig deeper. The other colleague described their team as one where the overwhelming majority of the questions seemed to be much more involved and offered many opportunities to collaborate with the field. While my role was to participate in the conversation and share observations from my own team’s experience, which, coincidentally does not resemble either of my colleagues’ teams’ experiences, I felt the urge to listen and see if I could potentially structure the challenge that was being described in a manner that would allow for a more structured conversation.

Through the conversation I was able to discern that, unbeknownst (SP???) to my colleagues, the conversation focused primarily on two areas that I think are important in being able to answer questions and solve problems:
– The nature and complexity of the question / problem. This can refer to either the specificity and clarity of the question (2+2 vs. if I sum two even numbers will I get 4), or the complexity of question (can you optimize the distribution of these points across distance, count, drive time, and traffic patterns).
– The sophistication of the tools, methods and knowledge available to answer said question.

For example a simple question like “What is 2+2?” can be easily answered because we have developed the tools and methods to calculate this. The question “How many Watts are needed to power these three devices?” is a bit more complex, but to those who have studied electricity and elementary physics are a lot easier to answer. This is due to their training which has been acquired. You can see the progression continue and get to questions that only extremely specialized individuals might even be able to begin to think about how to answer it.

To make things more complex, as individuals and teams grow, I believe that they want to have a “healthy” mix of these – well at least some do. I suspect that most people reading this will want to continue to develop their knowledge by solving and answering more and more complex questions, but that they also answer what they think are relatively simple questions on a regular basis. Satisfaction with your progress, I propose, is directly linked to the balance of being pushed and being comfortable. Different people will have different thresholds for what they consider a desirable state, but in general I would argue that they want both.

So I propose to you the following approach to thinking through complex problems.

Low Work /High Reward }{ High Work/ High Reward
Low Work/Low Reward }{ High Work / Low Reward
35% | 25%
35% | 5%
(Another article – how to balance over the development of a team)

As I develop my own thinking I would be delighted to get your thoughts on this framework


In thinking of this on a 2 by 2 matrix, I would argue that there are four positions:
– Codify: In a situation where questions are not very complex (“What is 14*11 squared?”), one can improve their knowledge to make answering these questions faster or easier. This can be done either by learning new knowledge on how to shortcut these types of questions, acquiring new tools (a calculator), or learning multiplication tables.

– Explore: In this area we are dealing with questions that are quite simple, but already have the tools. The opportunity here is to think about how can answer more sophisticated questions with the tools we have. EXAMPLE:

– Adjust: This is potentially the worst place to be. These are complex questions that we’re being asked to answer without the necessary knowledge, tools, and methods. Therefore our ability to answer those questions within any timeframe is fairly limited. For example, think of the highly unrealistic example of Sir Isaac Newton being asked to come up with a method for sending someone to the Moon. Even the best knowledge, tools and methods available at the time would not help in answering that question. It would take, after all, over 400 years for a human being to set foot on the moon. The advice for people with these types of questions if to find a why to shortcut the process and obtain the knowledge, methods and tools as fast as possible to get be able to answer the question, or (better) find a way to simplify (“ok we can’t get you to the Moon, but we can have you fly in a few years”).

– Innovate/Explore: This is a good place to be in. This is where research and development can really have an impact. This is the area where the tools, methods and knowledge are mature enough, and the problems remain complex enough that we can start explore the next S curve of tools, knowledge and methods. Overtime, questions answered here should migrate to the “codify” box.

Over time, questions in the Innovate category should make their way down to the Codify category (and hopefully t

How does this apply to NYTM:
In teams that seek to meet client demand, it’s important to have a healthy balance of work. I have found myself being involved with teams who too often are in the codify box and by trying to get to the innovate box (which, let’s face it, that where we want to be), end up derailed and thrown into the Adjust category. Recognizing this risk is a first step in organizing effective teams, managing balance between types of projects, and ensuring growth.

While I am using a 2 by 2 to represent this, I by no means believe projects and the nature of problem solving to be that simple. I fact, the process to move is much more iterative and “stepped”. A 2-by-2 is just an easy way to communicate this.

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