How I Use Data to Make Decisions

I love data. What I love even more is using data to drive decisions. Over the years I have shared my enthusiasm for data with anyone who would listen. This has included employers, employees, project teams, friends, family, budding entrepreneurs and even strangers while sitting at a hotel bar.

Now, I can summarize those thoughts into three guiding principals.

Guiding Principal #1 — Daily Disciple

I have been using Quicken to track my personal finances since 1995. For people who know me, they would call my love affair with Quicken an obsession. I have, on average, spent about 10-mins a day entering data, reviewing data and making data driven decisions with my Quicken file. This adds up to the equivalent of 60-days on my personal financial plan in the past 24-years.

Why the personal anecdote about Quicken? For me, it’s my best example of daily discipline. It’s the daily habit that allows me to take stock of where I am at financially in any given moment and allows me to make informed decisions on how to move forward.

This habit has carried over into my professional career.

Guiding Principal #2 — Focus on What is Important Right Now

Before I start mapping out which are my most important metrics right now, I reflect on three things.

  1. I acknowledge that there is too much data to actively evaluate.
  2. I understand that I need to spend the most time defining the right key metrics, ie) less=more.
  3. Just because I am focusing on key metrics does not mean I restrict data collection.

Too Much Data

One challenge is the abundance of data. Abundance of data usually creates two negative reactions. First it creates a paralysis in decision making. Second, it can be overwhelming which can make it difficult to stick with a daily habit. You know the saying; it’s about quality not quantity. This is key when talking about data.

Big Data Dashboard

Right Metrics/Right Time

It is important to filter out what are the most important metrics for ‘right now’ to make decisions. I personally aim for no more than 3 metrics at any given time. However, it is important to understand the key data elements behind your primary 3 metrics in case you need to go deep in terms of understanding cause/effect.

Data Collection

A focus on key metrics is different than the collection of data. Collection and storing of data in a structured format is important to drill down into the sub-metrics. This can help you understand cause/effects or as priorities shift can help you define a new set of key metrics to replace the old ones.

For example:

When I started using Quicken back in 1995 I focused on three key metrics.

  1. wealth creation, defined as assets minus liabilities
  2. % of income that went into investments
  3. how much interest I was paying

Quicken was the tool that allowed me to gain insights into deeply understanding how I made, spent and invested money. Over the years, my first 2 metrics have not changed. My third personal metric has changed every couple of years.

When I became the President of Mediative in 2014, it was a 100+ person company, doing $40M+ in revenue spanning Ad Network, Enterprise Service, and Shopping Marketing business units. I was fortunate that Mediative was very good at capturing and storing data. When I joined I heard a common theme around too much data and too many individual data points that made the business feel chaotic. The business unit metrics were important but there was a lack of transparent global metrics that made it difficult for the individual business units to realize how they intersected with each other. This in turn caused a challenge with employee morale. In order to regain growth at Mediative and make it a positive cash contributor, we needed to rally the entire organization across a common set of metrics that every business unit was invested in.

So how did we use the data to position ourselves into quicker decision making? We focused on three core metrics that would guide the organization: Revenue Growth, Margin Contribution and % of Publisher Commissions.

We ripped the entire business apart to understand revenue and margin by unit, product line and customer. The last one was related to our specific focus on representing our individual publishers as well as our owned and operated properties. Our secondary metrics tended to focus on product and client contributions. Our third level down related to human capital metrics related to product and client delivery. We could then connect every metric in the organization (whether sales, marketing, operations, HR etc.) in the context of these key metrics, which allowed us to surgically make decisions. By 2016 Mediative was close to a $50M business generating over 10% in EBITDA margin contribution and our employee satisfaction surveys became the best in the company.

Focusing on key metrics will help you narrow down the abundance of data and make it easier to create a daily habit of reviewing and actioning. You will need to go deep at times to understand why something is either over or under performing. If you pick the right core metrics, every micro metric will roll-up. If you cannot create a clean roll-up of data, then I would argue you don’t have the right key metrics.

Guiding Principal #3 — Transparency

Whether personally (with your spouse or loved ones) or professionally (with your shareholders or teams) transparency is key. In my experience transparency leads to 2 outcomes. First it allows everybody to own their portion of the problem clearly and second it allows everybody to question decisions that don’t align to the key metrics. The first is important so that people understand how what they do everyday impacts the key metrics. The second is important to eliminate opinions based on bias (i.e. hierarchy, politics, “squeaky wheel”, emotions) and gives everyone a chance to voice their opinion in an informed and productive manner.

My approach to the way that I manage and tackle data has been governed by the above guiding principals.

If you have additional thoughts, guiding principals or stories please share.