Logic tree and the Answer First Methodology
Contents |
Abstract
Problem solving in a company is difficult: Not only do you first have to identify a problem, but the company may also be so deeply entrenched in the way that they are doing things that they cannot possibly consider doing it differently. Developed by highly respected consultancy firms, The answer first methodology is a proven way of structuring a problem and the subsequent project activities in a way that is communicable, coherent, and thorough. By defining a problem as a primary assertion and working out from that, it is broken down into smaller, test-able fragments. What follows is a testing of the sub-assertions and whether proposed solutions will have an effect on the sub-assertion and through that the primary assertion. This breakdown enables a methodical, solution oriented and coherent project work where the main problem is always in focus. Framing the project around a primary assertion also creates a narrative that presentable and easy to follow for stakeholders. This article will briefly explain the birth of this methodology. Subsequently it will explain how it fits into the contemporary bigger picture of business management. What follows will be a crash-course in working with projects using the answer first methodology. This article will also highlight the pitfalls one can encounter when using this methodology as well as provide a general example throughout the presentation of the tool.
Introduction
Months of hard work have led to this fateful day where you are to present your findings to an audience of important stakeholders that comprises of executives, the CEO and your manager. The importance of this presentation to your career cannot be understated. Nervously you begin your presentation by walking through the data that your team believe to be the root of the problem. 10 minutes later, still muddling through the data, terror strikes you as the CEO sharply interjects: "How is this data at all relevant to the problem at hand? Listen, I have an important meeting with my lawyer in 5 minutes and you are still yet to present any actionable solution. Get to the point". Your hands become clammy with perspiration - this is not going as planned! "We cannot say for sure, sir, but we believe the problem has its' roots in this data, but further analysis might make us more certain" you nervously stutter. The CEO's gaze toward your manager says it all. "This is a waste of my time. Reach out to me when you can provide me with solutions rather than irrelevant gibberish". Frustration painted in his face, the CEO takes his leave while regretting to trust in-house specialists in this task as supposed to outside consultants.
Sooner or later, each and every one of us will, like the above situation, have to be presented with the task of communicating a complex problem and its' solution to important people. Unfortunately, solving and communicating complex problems is not easy. As a company machine grows, the cogs and gears comprising the engine are increasingly interconnected - as such the complexity of problems are bound to increase. This further complicates concise and logical communication of the problem.
In order to tackle the problem of solving problems of increased complexity and avoid situations described above some of the worlds biggest management companies McKinsey and Bain & Co. developed a structured problem solving methodology (Bain, McKinsey). The methodology, despite having distinct names, follow the same principles - understand and frame the problem and context, define an initial hypothesis/answer, break down the answer into analysable elements and lastly validate or invalidate the initial hypothesis/answer.
This article will present the Big Idea of the methodology, followed by a crash-course in the application and context to other contemporary approaches like systems-oriented problem solving. Lastly limitations and further reading will be discussed.
Big Idea
1: The Logic Tree and The Answer First Methodology is a brilliant way to structure and communicate complex problems
What better way to further communicate and exemplify that the Logic tree and the Answer First Methodology is a brilliant way to structure and communicate complex problems, than use the methodology as a framework to explain itself! If this methodology is successful in communicating itself, it will no doubt be a useful tool to managers or prospective engineers too.
What comes first is the Initial hypothesis. This hypothesis not only lays a foundation for further exploration within the problem owners’ area of solution, but also provides a solution to the problem from the get-go. That's right - you answer the problem before you have even done any analysis or research!
2: Communicating the problem and its respective solution(s) is clear and concise
A paramount facet of dealing with business problems, and one of which the success of the project according to PMI standards [PMI Project standard] is contingent on, is communicating them to stakeholders and the project team. The elevator test [McKinsey way] states that a problem solver post-analysis should strive to be able to communicate a complex problem and its’ solutions over the course of an elevator ride. For you ‘stair people’ out there that is approximately 30 seconds. ‘Why?’ You may ask. The reason is two-fold: 1. For you to be able to boil a complex problem and its’ solutions down to 30 seconds requires a thorough comprehension of the essentialities within each of them. 2. Important stakeholders as well as the problem owner, be it manager or executive, whom are either responsible for change or can give you the mandate to implement a change simply does not have time to engage in the problem like you have. It is your job to present to him/her the essentialities of your findings [Mckinsey]. This methodology enables exactly that.
2.1: Logic tree enables reasoning with a clear structure
Using a model as an illustration will greatly aid your communicative efforts to get your point across by illustrating complex interrelated information in a simple way (In the company of others). The Logic Tree is no different. Providing a hierarchy and structure to your communication that can at all times be referred to enables the target audience to clearly follow the points of your presentation and the thought process behind different assertions and how they relate (the pyramid principle).
2.1.1: Attention is kept! No muddling in non-relevant gibberish
In a study, 182 senior managers were interviewed in a range of industries, 71% said meetings are often unproductive (HBR). Using this tool, only stuff that is has an impact on the initial hypothesis is communicated. This avoids the communicator and the conversation straying into non-relevant gibberish, staying on topic. The overview the Logic Tree provides serves as a brilliant guide as to how the project is progressing (eg. We are currently examining this tertiary hypothesis) to and what the goal of a given meeting is, keeping attention on the problem at hand. [Mckinsey]
2.1.2: Reasoning is traced from the tertiary assertion to the initial hypothesis
Throughout the communication the reasoning is traced from the Initial hypothesis down the Logic Tree all the way to the Tertiary assertions. What follows is a data-driven and fact-based verification in order to analyse to what extent these assertions hold true. If they do, logical conclusions can now be made from the tertiary assertions all the way to the initial hypothesis. In this case – if data or facts support that 2.1.1 and 2.1.2 is true, a logical conclusion follows that 2.1 is true.
2.2: Answer First Methodology defines concise and communicable objectives
The Answer First Methodology utilizes deductive reasoning to arrive at a pressure-tested and actionable solution. Deductive reasoning sets itself apart by being thoughts that yield a conclusion from assertions being valid or not. This way of reasoning is very familiar because we do it every single day when considering day-to-day choices: “I don’t want to arrive late to work tomorrow, so I better set an alarm and mentally prepare my morning routine”. Here it is implied that the general conclusion one is not late to work is true if the premises that one sets ones’ alarm and one mentally prepare ones’ morning routine are valid. This methodology hereby presents general conclusions – assertions – that when broken down are proven and as such affirm the assertions higher levels or dis-proven and in this case require a re-formulation or a complete dismissal of the assertion.
2.2.1: Data is only presented to relevant and verifable tertiary assertions
Data is only presented to relevant and verifiable tertiary assertions To drive a concise communication it can be assessed which tertiary assertion that has the highest impact on the initial hypothesis (Mckinsey) – and then the data for this assertion can be put forward to prove why a certain assertion is valid. The Logic Tree also clearly presents what assertion the shown data verifies – avoiding the pitfall of showing data that confuses the audience more than it backs up your points.
2.2.2: Conclusions and hence solutions are clear in any stage of the project
A major strength of this methodology is that solutions are always present, just under different degrees of verifiability (Mckinsey). This means that, in principle, at any point stakeholder can inquire into the findings of your analysis and get a usable answer. In contrast, problems solving that is done by way of inductive reasoning need to have a high degree of the quantitative analysis done in order to draw any valid conclusion (Pyramid).
3: Solving complex problems is done in a structured and coherent manner
Solving multi-faceted, complex problems is not easy. By using this methodology, clear objectives – goals - with their relations are clearly presented. The closer to the main hypothesis, the more vague and general the assertions are – as such these cannot be evidently dis-proven or proven [Mckinsey] but have to be broken down into smaller, testable tertiary assertions. They do, however, tie the logic between the initial hypothesis and the factually verified tertiary assertions to create a coherent and easy-to-follow reasoning.
3.1: Complex problems are broken down into manageable and actionable sizes
A recognized method to solve complex problems (also seen in System-oriented problem solving and the Black-box tool [no more muddling through]) is breaking it down into smaller, more manageable sizes. To do so we must deduct, discuss, and investigate with colleagues – what is they key element of each hypothesis? For this, a good question to for each step to ask is ‘Why?’. Assertion: Why does the Logic Tree and the Answer First Methodology ensure problem solving is done in a structured and coherent manner? …. Answer: The problems are broken into manageable sizes. And why does this fact ensure the former… ->
3.1.1: Focused data gathering - fact based assessment of tertiary assertions
The search for solutions is only manageable if it is known what to look for.” (No more muddling through) When the problem has been properly de-constructed, focused data-gathering is commenced. Making sure to only do data-collection for the ‘lowest’ level of problems ensures a clear objective when gathering and analysing data that can validate or invalidate an assertion. Not only that, but a sensitivity assessment can also be assigned to each tertiary assertion determining how much they affect the parent assertions and in turn the initial hypothesis.
3.1.2: Logic tree as a basis for a structured workplan
As a framework for a detailed workplan, the Logic tree can be utilized to manage a teams toward a solution. By using the Logic Tree as roadmap of activities, a project manager can utilize Primary, Secondary, and Tertiary assertion as milestones (Bain). It is important to note, however, that this methodology is not a project management tool per se. To properly manage a project it is therefore recommended to use other managerial tools such as the GANNT chart or SCRUM to manage the completion of tasks and day-to-day activities in conjunction with this methodology.
3.2: MECE
A term leading consultancy companies using this tool swear by is MECE. At McKinsey, It is hammered into every graduate’s brain [Mckinsey]. In context of this methodology, the use is straightforward - in the development of the logic tree, each assertion must address the previous one in a unique way. Not only that, but the sum of all sub-assertions under every assertion must also be Collectively Exhaustive of all relevant impacts. [McKinsey]
3.2.1: Each assertion must be unique – avoid double work!
By having every assertion be unique, the problem-solving group mitigates the risk of double work, or even worse, that two non-unique tertiary assertions validates contradicting assertions.
3.2.2: Leave no stone unturned – all possible solutions/causes are analysed
By having a Collectively Exhaustive list of assertion, no stone is left unturned. This means that all possible solutions are pressure-tested for impact on assertions.
Context and Application
A strength of this tool is its' scalability, allowing it to be utilized in both project, program and portfolio management. Being able to adjust the generalization level of the initial hypothesis to the level of the problem can scope this tool to fit the desired problem [McKinsey].
In this example, the scope of programs, portfolios and projects in this makeup car manufacturer BS Auto is derived from the overall strategic/business goal of wanting to gain EV (Electronic Vehicles) market share within the car industry eg. the portfolio scope should be 'Model insert-fancy-model-name-here'. Similarly, program and project scopes can be derived from the logic tree that is developed from the answer-first assertions in the logic tree.
In system-oriented problem solving context
As it happens, this methodology fits neatly into the system-oriented problem solving method. In fact, literature suggests that Answer First principles and structure is a good idea to implement while approaching goal definition and concept synthesis in the system-oriented project solving process:
"The result of the goal definition of objectives. This catalogue of objectives is further used in the concept analysis and selection"
As such, it is recommended to use the Logic Tree as a way to clearly structure objectives as solutions to the initial hypothesis.
"In the first step of a synthesis-analysis-cycle, a wide and comprehensive range of solutions is developed with only a shallow description of the details. This first step aims at completely covering the field of possible solutions"
"At the beginning of the search for ideas it is advisable to write down some fundamental solutions"
Limitations
Text
