A decision-making hack to avoid drowning in data
Original Publish Date: Oct 28, 2020
Do you have a system for collecting the right information to make decisions?
Leaders often drink from a firehose of data points fed to them from different teams. It’s worth thinking about how many of these data points lead to “sound” decisions.
We have a human need to accumulate. This bleeds into the need to amass troves of data hoping our decisions will get better. Sometimes this is an excuse to prolong decisions. Sometimes this is an effort to try hopelessly to feel some control in the decision-making process.
We must accept one thing. There’s no way we are ever going to have every single piece of data to make our decisions. Stop aiming to collect every data point. Our goal shouldn’t be to “boil the ocean” to use a cliché. While collecting data can be fun, our goal should be to determine our “minimum viable version of data” that helps us make smart decisions and keeps the ball rolling.
To phrase the initial question slightly differently – do you have a system to make smarter and faster decisions?
I want to offer a simple framework adapted from a market research philosophy called “Backward Market Research” which “rests on the premise that the best way to design usable research is to start where the process usually ends and then work backward”.
I find this philosophy helpful in streamlining my research/decision-making process no matter where I need to investigate to find the right information for my decisions.
Let’s look at a simplified way of applying the ‘backward market research’ philosophy to your day-to-day decision making.
STEP #1: Start with the decisions you want to make
Start with the list of decisions you want to make and work your way back. Some of us might be eager to exploit our proclivity to analyze and research data right from the get-go. Listing out the different decisions helps carve out a direction to the research process.
How do you tease out the decisions you’re truly trying to make?
Use this short exercise to recalibrate your brain and pencil down the actual decisions. Assume that you have all the data in the world in a report in front of you. Now ask yourself the following questions,
What will all this information help me do?
How can I apply these results?
The decisions you’re trying to make are the answers to these questions!
STEP #2: Figure out the right, minimum number of data points to make those decisions
We rely on too many systems generating a multitude of data points that forces us to look at redundant information sometimes. You can figure out the data points you need by reviewing the list of decisions from the previous step here.
The catch here is to not go overboard trying to collect way too many data points. Hence, the keywords here are “right” and “minimum”.
What data points or pieces of information do you need to make the decisions you uncovered from the first step? What’s the minimum information you need to make these decisions? These two questions go hand in hand.
STEP #3: Create the appropriate questions to uncover those data points
This might seem like an extra step, but I find this crucial in deciding how I find my answers.
The previous step offers you a list of data points or pieces of information that you’re looking for to make your decisions. This added step forces you to articulate your questions (irrespective of who you’re directing it to) that would uncover the data points you seek.
You’re now perfectly primed to figure out the sources to answer these questions by making the journey from decisions to data points to questions by this point.
STEP #4: Use the most effective source(s) to answer those questions
Your prepared set of questions should give you the answers you want. The sources you rely on to answer those questions can change on a variety of factors like timeline, cost, detail, stakeholders, etc.
There are two major sources you can rely on to generate answers for your questions after accounting for the factors: (1) primary sources, (2) secondary sources.
Primary sources include direct interactions with the folks who can offer you the answers you’re looking for. Doesn’t matter if they’re your colleagues, employees, customers, users. These “interactions” can take the form of surveys, interviews, workshops, focus groups, observations.
Secondary sources can incorporate different buckets of information. For example – (1) public domain data from think tanks, consulting companies, (2) company data like earnings calls, annual reports, investor presentations, (3) third-party/subscription data – ex: market research firms.
A quick example of the framework in action
Assume that you are part of a B2B marketing team that must review its spending every year and reallocate the team’s budget primarily to efforts that offer better leads, win rates, referrals to name a few. Your team works with inside and outside sales folks, maybe even with agents and distributors in certain scenarios. You rely on them tangibly to understand how successful your efforts are in generating new revenue.
We can use the 4-step framework to work through one potential decision in this example.
Decision: allocate marketing spend effectively to the well-performing sales and marketing tools
Data points: leads, wins by sales and marketing tools currently in use
Question: which sales and marketing tools currently in use are the most effective (by leads, by wins) in every region we operate?
Source: internal poll/survey aimed at inside and outside sales, agents, distributors which includes this question and offers the tools currently in use as multi-select options
Again, this example can look different depending on your company, markets of interest, industry, sector. This example is more about the flow and the process.
We have an eagerness to jump into the research process anytime we’re unclear. Our efforts therefore can be all over the place with no structure or rhyme or reason. Starting with the decisions you want to make narrows down your focus and helps you make smarter decisions in a consistent and fast manner.