What do you need to know before starting a business?
Great question, Roger Martin has the right answers! Successful businesses are both adept at imagining new futures and doing what is necessary to make them happen.
He redefines what it means to be a “designer” as we learn that design thinking is the process of working your way down from mystery to heuristic and algorithm.In order for businesses to produce the most wealth, they must have the knowledge and skill balance between working on current problems with an eye on future ones.
One of the original creators of algorithms, it may come as a surprise to learn, was McDonald’s. Ray Croc didn’t start with the McDonald’s that many people know and love today; he started with a mystery before driving it down into an algorithm so that a Big Mac in New York is no different from one.
We need to stop thinking and acting in the same way as previous generations, but this is difficult too.
Martin believes that the only way to live a fulfilling life is to become opposable--to stop doing what everyone does, and take time for yourself to do something uniquely you.
The most important thing you’ll learn is how to turn design thinking into a sustainable competitive advantage – the ultimate goal being to fill your bank account.
Design with care and precision, and one day you may rule the world.
Part I - The Knowledge Funnel and Design Thinking
Some companies earn more than others, and I’d like to be part of those that do. Forget about HR and finance courses, a psychology degree is the key to success.
There are two ways in which you can think. Analytical thinking is about seeking certainties, while intuitive thinking relies on the art of knowing.
Companies are great at maintaining their culture as it grows in size and scale, but this prevents them from making the necessary changes to innovate.
Intuitive thinkers may be incapable of systematizing what they do, but are well-suited to imagining new futures.
To achieve long-term financial success, one must employ both short and long-term thinking. In order to navigate the knowledge funnel, both types of thinking are required.
The Knowledge Funnel
The knowledge funnel is divided into three parts.
Mystery is the first step in the funnel, which may take on a variety of forms. Asking questions is the goal of this stage. For instance, McDonald's asked "What would Americans like to eat on the go?"
Heuristics are the second stage of the funnel approach, and allow us to break down a mystery into generalized rules.
McDonald's went from mystery to heuristic when they attempted to create a quick-service hamburger joint that appealed to Americans. Heuristics are techniques that prompt us towards an answer by exploring various possibilities.
Lastly, how knowledge is conceived into an algorithm illustrates a process that starts at the top of the funnel and takes shape as it goes. For example, when McDonalds turned its business operations into a fixed formula (cook burgers with this equipment, at this temperature and for this length of time), in effect the company created an algorithm.
Algorithms are a set of predetermined steps that can be followed to generate predictable results. This is useful for hiring unskilled workers for jobs traditionally handled by skilled labor.
The competitiveness of an algorithm allows for significant monetary gain with a short-term profit that is higher than their competitors.
Your earnings will accumulate quickly, leaving money available to invest in a new mystery. Why start over?
Because you must update any algorithm as the world changes, your solution to a problem may become obsolete.
For example, your competitor takes on the mystery that created your original heuristic and creates one even more powerful.
Design Thinking
This means you're going to have to focus on exploration and exploitation at the same time, which is understandably difficult. In order to do this well, it's important that you're able to engage in design thinking or become a 'first class noticer.'
IDEO’s design expert Tim Brown, says that design thinking is a process for matching people’s needs to what is technologically feasible and turning it into customer value. The root of good design is abductive reasoning, which can involve coming up with the best possible ideas for a particular project.
However, most of the world sees "creative types" as flighty people with little respect for cadence and deadlines. And in some sense they're right-- but when we consider the good in these things, it is easy to see that anything offbeat must be suspect.
Designers use inductive and abductive reasoning to find patterns in the amorphous whole that others might not see yet. While exploring, there are many false starts before finding the right inference. This type of exploration can be expensive and risky at times but has great rewards for those willing to take on the risks. Design thinking is about moving knowledge down the creative route.
Part II - What gets in the way of design thinking.
Business is inherently faced with a tension between the need for reliability versus validity. While reliability focuses on consistency and dependability, validity focusses on producing meets desired objectives. Although the algorithm provides a quick monetary return, most organizations make the mistake of running that algorithm blindly and fall in love with its predictability.
It’s understandable why time frames are difficult to define for the company. Overweighting reliability drives the pursuit of validity out and emphasizes routine work as a result.
Getting Stuck in the Algorithm
The three main forces at play in organizations when seeking reliability over validity are: The persistence of the past: even for successful organizations, at some point they must show that their strategy is going to produce a particular ROI.
When you need to prove something, the best way is by comparing your future actions with the past. Let’s look at an example of how not to do this correctly.
Ten years ago, GM's marketing team wanted to publicly prove they should market only SUVs. They cited ten years of data from the past and have what they want. Naturally with this history, GM would be proven wrong in their decision.
Another approach would have been to request that those funds be allocated into smaller, more efficient vehicles because we believed that this is where the market would head. We had data to back up this case but often stipulations based on past experience supersede proposals which can only be proven by the passage of time.
The end goal of 21st century management is to remove judgment from decisions, but this is challenging because many things are not easy to automate. Credit scoring systems and insurance pricing algorithms are good examples, as well as marketing systems like Amazon’s product recommendations service.
The attempt to make AI bias free sometimes doesn't produce the desired result.
The pressure of time: a reliable system saves quite a bit of time. Take, for example, the advent of automated asset allocation systems at investment advisories. Algorithms have replaced the judgment-heavy process of making a portfolio recommendation.
Not knowing of the existence of a machine: there are many scenarios in which machines could be doing the work of an employee. It’s probably common knowledge that treating people well and with respect is a cost-efficient investment. Martin uses the example of a retail store manager manually creating a schedule each week. You could also think about all the work that was done creating mailing lists, which is now automated by email marketing software and programs.
Getting stuck in a heuristic
Algorithms are complicated, and getting access to them can be challenging. This difficulty is partly because algorithms are usually inaccessible in the heads of highly paid executives. If they work to create an algorithm that could do what they do, the company would no longer need their services. They’ve broken down the concepts and turned them into smaller parts that can be done by employees who are paid less.
Hiring someone who is willing to take on heuristics and automate them into algorithms will be worth 1000 times more to your organization than the employee who says "It can't be done". Are you going to fire somebody for bringing that much value?
Wouldn’t you want to get them working on taking the next heuristic and turning it into an algorithm? Yeah, I thought so. If it sounds heartless or "so 80's", well, don't worry! It will make much more money than committees who come up with solutions.
Part III - Building design thinking into your organization
Sure, this all sounds great, but what about getting the whole company to adopt design thinking? Have you considered sending out a memo? That might work, but an even better alternative is to implement these ideas across your organization.
If you work in a larger organization where you are trying to gain support, begin by establishing your expectations and get the boss on board. Initiatives often fail because the boss doesn't seem to be committed.
Design thinking is challenging to sell because the value it brings isn't as easy to measure as a Six Sigma process. The benefits grow over time, and you need top-level support for implementation. You can’t start without it.
As Claudia Kotchka, who got design thinking off the ground at P&G, said, “it takes at least ten years to get mastery in design.” When it comes to building a successful business, time is of the essence and you do not have ten-plus years with which to start creating results.
Implementing these strategies may seem easy, but be prepared for some detours and bumps along the way. Trying to make this change without resistance won’t work. It’s important to use your design thinking skills to anticipate what might go wrong and plan alternatives in advance.
With design thinking, the transformative effects can’t be explained with reports and presentations, they need to be experienced in person.
Demonstrate your ideas as often as you can to make them feel like active participants rather than passive observers.
So, there you have it. All the information you need to take into account when applying design thinking strategies in your next campaign.
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