Dr. Mario's 2nd 🧠

Delivering Value as a Data Team

3 min read

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Any and all analytics focused on just answering questions or building dashboards is doomed to becoming a low value cost center in the organization, which eventually leads to the dreaded “what’s the ROI of the data team?” question. (View Highlight)

Another more insidious trap is focusing on “insights” especially “actionable insights (View Highlight)

I’ve mentioned it before that the real value of the data team lies in driving operational performance that can be measured directly in the bottom line based on actions taken. But how do you do that? (View Highlight)

You have to understand that there are three tiers of value for data teams:

  1. Measuring current performance accurately
  2. Research & development
  3. Data driven automation (View Highlight)

Upon joining a company as head of data, you’ll feel an immense pressure to answer questions but as I’ve said before, this is a trap (View Highlight)

Start by making a list of all the metrics that a SaaS company needs to measure. SOMA has a very comprehensive list you can use. Use this as a checklist to interview all the executives and figure out what exists already and what needs to be built. For the metrics that do exist, check their definitions and formulas against SOMA. (View Highlight)

Many of the questions you get from stakeholders are answered through the metrics and data sets delivered as Tier 1 value, but there are some questions that are best framed as research. This is a key distinction because it sets up the proper expectations with stakeholders (View Highlight)

discovering causal or correlational drivers to key output metrics from Tier 1 should occupy a good portion of this work. Amazon calls these controllable input metrics. (View Highlight)

Here are a few other types projects that fit this category: • LTV modeling • Multi-touch attribution modeling • Marketing mix modeling • Lead scoring • Identity matching from anonymous data • Marketing segmentation • Recommender systems • etc. (View Highlight)

while the value is tangible, they don’t fit into the production paradigm as easily so be careful about shoving this type of work into the agile framework. (View Highlight)

For example if you’ve done lead scoring or LTV modeling and then used that output as input to a process that decides whether to call them or email them, you’ve done data driven automation. (View Highlight)

• Sending automated emails to for abandoned shopping carts • Sending automated emails with customized promotions • Sending automated reminder emails/texts for appointments • Automatically sending high/low LTV leads into a separate funnels • Raising an alert when sales are too low for the day • Generating a mailing/email list of customers for a special promotion • Anomaly detection automation • etc. (View Highlight)

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