Main illustration: Gabi Zuniga
Your decision-making process is slowing you down.
Speed is every startup’s biggest competitive advantage. We know that moving at speed is all about making decisions quickly and acting on them – but quick decisions get a bad rap.
They’re considered heedless, overly luck-dependent, and almost treasonous by those of us in the data and research domains. Still, effective, quick decision-making is a skill we crave and can increase agility, energy, and momentum within any team.
Recent research I’ve conducted with Lynsey Duncan has really helped sharpen our thinking about this process – here, we’ll reveal some of the lessons we learned to help you become a better, faster decision-maker.
The challenges of quick decision-making
Improving our decision-making process carries two key challenges. The first is identifying what information to use as inputs to the decision; the second is improving the way our decisions influence outcomes.
The intuition, experience, and motivations of the decision-maker are critical inputs to the decision. This may seem counter-intuitive, but they are as important as evidence, facts, and data. Both play their part – it’s a purposeful consideration about how each of these types of information drive you towards making the best decision in the shortest possible time frame. A great decision-making process empowers this.
“Outcomes are important, but it’s difficult to extract valuable learnings from them. We learn far more by studying the decision itself”
The second challenge is implementing a feedback loop. Outcomes are important, but it’s difficult to extract valuable learnings from them. We learn far more by studying the decision itself and questioning (independent of the outcome) whether the best decision was made at the time. Luck always plays a role, the question is how big a role.
Start with these decision-making principles
There are a few key points to remember when you have a decision you need to make quickly. First, ask yourself if you’re actually making a decision. Making a decision means choosing from a set of alternative courses of action to address a particular problem or opportunity. Consider these four principles; each one plays an important part in your decision-making process.
- Know your problem: You must have clarity on the problem before deciding on how best to address it.
- Lots of small decisions are better than fewer large decisions: Too many of the decisions we make are unnecessarily large or require too much evidence for us to proceed quickly. Large decisions are risky; break them down into a set of smaller decisions or actionable experiments.
- Make a decision as early as possible and use the decision-making process to iterate and improve on that decision.
- Continuously review your assumptions and find your blind spots. Rapid learning and course correction is a key part of an agile decision-making process.
A six-stage decision-making process
Stage 1: Define the dilemma
The first stage of any decision-making process is to define why you are making a decision. What is the dilemma this decision will address, and what future are you trying to create with this decision?
Progress can be slow if the decision-maker lacks a firm grasp on the reason for the decision, i.e. the specific dilemma or problem is not clear or the desired outcome is not well understood.
Stage 2: What is your “default decision”?
Once you understand the problem you are trying to address, decide what you would choose if you had to make the decision right now, without considering any further evidence. Cassie Kozyrkov, Chief Decision Scientist at Google, calls this the “default decision” and identifies it as the first thing great decision-makers do.
The default decision encapsulates what the decision-maker knows right now, introducing the valuable expertise, motivations, experience, and objectives of the decision-maker. It establishes a decision early in the process and becomes a benchmark against which we evaluate new choices.
Failing to identify a default decision slows down decision-makers because:
- They try to gather as much information as they can before having a valuable purpose for it. These broad information-gathering exercises are typically an inefficient, cumbersome, and unnecessary step.
- They consciously try to exclude their own expertise, intuition, and objectives from the process. The decision-maker is rarely starting from a blank slate or first principles, so experience and expertise are as valuable as facts and data at this stage.
Stage 3: Do you need more evidence?
Research has a specific purpose in a decision-making process – its role is to reduce uncertainty and identify meaningful choices.
“There is a risk of getting lost in time-consuming, detailed research that is interesting but not specifically relevant”
Decision-makers often slow down at this point because they lack targeted research questions with a specific purpose. There is a risk of getting lost in time-consuming, detailed research that is interesting but not specifically relevant, and just serves to bloat the decision-making process.
This stage centers around one important question: what information, if available, would steer you away from your default decision? What would a better option look like? For example, would you make a different choice if you knew development would be quicker, or if you were sure it would deliver better customer retention?
These attributes of a better decision can be converted into highly specific research questions (e.g, what features can we develop in less than three months that we are confident will improve customer retention by more than 5%?).
Stage 4: Identify your decision choices
From the research and insights collected in Stage 3, identify your set of decision choices. Each of these should represent a meaningful candidate for selection – eliminate any choices you are unlikely to select.
At this stage, it’s common to slow the process by identifying too many choices, or worse still, attempting to identify all possible choices. It’s easy to feel like the “perfect choice” is still out there or that there are options you may have missed. Of course this is possible, but if you’ve given thoughtful consideration to the dilemma and conducted targeted research, it’s unlikely. Trust the process, and yourself.
Stage 5: Make the decision
Choosing between your set of identified options is a case of risk versus reward.
For each of the decision choices, what are:
- The associated opportunities: How would this choice help to realize these opportunities?
- The associated risks: How might those risks manifest themselves?
There are two critical outputs of this stage:
- The decision itself, based on the decision-makers opportunity/risk assessment of the “best” choice.
- The documented rationale for this particular choice: What assumptions are involved? How will that choice deliver the opportunity, and how confident are you that it will? What are the associated risks and what level of risk do they represent?
You may not have high confidence in these assumptions, risks, and opportunities at this stage, but it’s important to record the understanding at the time the decision was made.
Stage 6: Review the decision
The final stage of an effective, quick decision-making process is developing a constructive, actionable feedback loop.
There are two important phases here.
- Review the outcome: Ask yourself whether you achieved your goal, addressed the decision dilemma, and created the future you intended with this decision.
- Review the decision: Regardless of the outcome, did you make the best possible decision at the time? Did the assumptions identified in Stage 5 play out? Did the outcome come about in the way you expected? What blind spots did the decision-maker have while making the decision, and what information – if available at the time – would have facilitated a better decision?
Reviewing the decision independent of the outcome is the critical learning point for improving decision-making skills.
“Great outcomes are not always the result of great decisions – to improve as a decision-maker you need to study how your decision-making process influenced that outcome”
Great outcomes are not always the result of great decisions – to improve as a decision-maker you need to study how your decision-making process influenced that outcome.
Becoming a great decision-maker
Great decision-makers move quickly by relying on trends, indicators, and their own experience rather than depending on deep research and first principles every time.
They judge themselves on making the best possible decision at the time, rather than focusing only on the outcomes their decisions deliver. These decision-makers focus on many small decisions, experimenting to make sure they’re right more than they’re wrong, and developing processes to course correct and learn when things don’t work out as they expect.
The most reliable sign you’ve become a great decision-maker? You’ll be asked to make more and more important decisions within your team and company.
At Intercom, the Research, Analytics & Data Science (a.k.a. RAD) function exists to help drive effective, evidence-based decision making. If you’re interested in helping drive the best decisions using research and data science at a fast growing company – we’d love to hear from you.