What you know is not as important as how you think. 

Neil deGrasse Tyson

As strategy, design, and engineering consultants, our team at Method gets to answer some of the most multifaceted product and customer problems businesses are facing on a daily basis. We are asked questions like, “How can we reduce customer churn?” and “What product opportunities will help us acquire new customer segments?” We are trusted with problems such as poor customer satisfaction or an undefined value proposition for a new market. 

 These are problems with a high degree of uncertainty, where outcomes are often difficult to anticipate and measure. Solving them is impossible in a silo; the process must involve nearly every department across the business. Moreover, whichever proposed solution(s) the business lands on must cater to multiple dimensions, from customer desirability to business viability, environmental sustainability, and technical feasibility.  

 We need to consider fast-moving technology, complex business models, soaring customer expectations, and societal shifts in attitudes towards brands’ sustainable and equitable responsibilities. And we often need to do this within a 10-12 week engagement.

 So how do we address this complexity with such speed? We come as learners, not experts. At Method, uncertainty is always an opportunity. We use it as a material and work through it with a flexible six-step framework. Here, we share how we bring down the uncertainty of complex business asks and rapidly arrive at desirable, viable, feasible, equitable, and sustainable solutions.  

 Step 1. Understanding the problem space

 Prior to the start of the project, we work with our clients to understand and frame the “problem space.”. This means that we define the problem, for whom it matters, and how we’ll know if we’ve solved it. We gain a deep understanding of how our client’s business works, its constraints, and the key concerns of its stakeholders. This enables us to define how fast our team needs to understand the problem, how many decisions the team needs to make along the way, and how much time the team members have to think through a solution.

 Step 2. Bringing the right team to solve the problem

 Although we employ a human-centered design lens, our project briefs often cannot be solved by the design discipline in isolation.  We need to consider all the other components, including business, data, technology, operational infrastructure, and human capital. The number of disciplines involved in a single project is usually in direct proportion to the number of decisions that the team needs to make. 

 Typically, this is a team of experience designers, product strategists, business designers, data scientists, engineers, system architects, and a project manager. Part of the project manager’s role is to identify whether the right team is in place to work around the problem space and make sure they have all the resources required. 

 Step 3. Tackling risks upfront

 Very early on in a project, we establish where the risks are in the problem space and rapidly iterate through ideas to evaluate them from desirability, usability, feasibility, and sustainability perspectives: 

  • Will people buy this product or choose to switch from another business? 
  • How difficult is it to build? 
  • Will this meet our business goals?  
  • Is this a sustainable solution for our planet? 

 We start with a minimum viable idea that we can put in front of customers to collect feedback. 

 For example, it could be a value proposition that is phrased in the form of a sentence or an experience principle derived from attitudinal and behavioral questions. We will then go through multiple rounds of validation with both stakeholders and customers. This is how we move so quickly. 

 Step 4. Sequencing, iterating and building upon decisions 

 In order for a multidisciplinary team to iterate with speed around the problem space, we plan team activities in a sequential fashion where every activity per discipline has:

  • a prerequisite (what is required for this task to begin), 
  • objectives (what do we need to achieve during this task), 
  • and capabilities gained (what did we gain after executing the objective). 

 The capabilities gained from one workstream feed into another workstream’s objective and become a prerequisite for that work to be executed. Commonly, the number of project steps will equate to the number of major decisions that need to be made along the way.  

 How quickly the activities need to happen in succession will depend on how big or risky the decision is around the problem space. Some big decisions require more thinking and testing space; others can involve only a few disciplines. Apart from team decision-making, there are also key decision points where business or customer input is required. 

 Step 5. Leveraging the right research tools at the right time

 We quantify business or customer input in two primary ways: 

  1. Conducting an ethnographic qualitative study to come up with an initial hypothesis that we test at scale using data science methods. 
  2. Conducting large-scale data mining exercises to identify specific trends per target group that we validate via qualitative studies

 Sequencing qualitative research and data science enable us to rapidly prototype through our minimum viable ideas with both business stakeholders and direct customers. 

 As we prototype, we move from Why do customers do what they do? to How do customers do what they do? Essentially, we use qualitative research methods to understand what is the customer’s purpose or desired outcome, why they initiate, continue or terminate a certain behavior at a particular time. We use quantitative methods to expose what process they follow in order to achieve their desired outcome in response to a particular situation or change. 

 Step 6. Keeping ourselves accountable  

 Every strategy project is just the beginning of long-term engagement with our clients. Since we aim to design what the future of the business becomes, we keep ourselves accountable in service of the final output; i.e. did we actually solve the problem? 

 At the end of the strategy phase, we commonly deliver design prototypes or business cases, supported by high-level engineering scoping and data assets. These act as stepping stones for our clients to start owning and socializing within their business to attract extra support and additional funding and commence the design & build phase.   

Technology is not static so our tools, processes, and thinking shouldn’t be, either. As a strategy, design, and engineering consultancy, we are not ready with a bank of answers for every business problem across each industry. Instead, we invest in learning, immersing ourselves in the problem space with creative approaches, analytical approaches, and the right team.  

 As Neil deGrasse Tyson says, “What you know is not as important as how you think.”