CU Employee

Strategy Creation

At the summit last week, there were many good ideas for first projects. We are working towards our first project, but it seems we shoudl first formalize our "strategy". Those short and long term items and goals.

Has anyone created a document like this?

You need to be a member of Credit Union Data Analytics and Digital Transformation Community to add comments!

Join Credit Union Data Analytics and Digital Transformation Community

Email me when people reply –


  • CU Employee Community Chair

    Heya Kurt,

    STCU manages a strategic analytics roadmap that plots trajectories mostly in three areas — BI for management, BI for member experiences, and BI for the future. In the first bucket we document our intentions for dashboarding and other initiatives that focus on data-enhanced decisionmaking. In the second is where we account for projects that bring data to bear on improving member interactions — 360-degree view efforts and next-best-product work and analytics for chatbots and others. The last category is for initiatives that are even further out — ideas that are 24 to 48 months out, and often include partnership explorations.

    It's a way of thinking that's morphed from some thinking I did many months back. But that's certainly not the only (or perhaps not even the best) approach. Another interesting way to map out analytics value for planning purposes is to document how your energies are going to be invested in a somewhat different three categories.

    I call the first one"what gets measured gets done" — and this, to be honest, is where a lot of credit unions start on their analytics journey, because it's the easiest concept for many management teams to get their heads around. Most organizations are tracking lots of metrics, sometimes within siloes and sometimes with less-than-precise measurements. The strategic focus in this area is identifying better and more consistent measurements of operational performance, given analytics investments. The objective is still the same — using data to help set smarter goals and then hold folks accountable to hitting them.

    The second class of analytics investment is "efficiency efforts." The idea here is to use data to help SAVE the credit union money, and organizations where Risk or Audit or Finance provide the executive sponsorship for analytics often put a premium on this work. It's all about using data to automate inefficient processes, squeeze hours out of work weeks, and success is measured by how many FTEs the organization didn't have to hire on its path to greater growth because of the cleverness of the data handling.

    The third and final area is analytics investment for "growth." The idea hear is to use data to MAKE the credit union money, and you see this most prominent when marketing or sales teams are driving analytics at the top. Here you'll find investments in modelling member behavior and purchase intent and all brands of communications experimentation. The notion is that data is a critical element to getting the right offer through the right channel to the right audience.

    A great many strategic roadmaps for analytics zero in quickly on the technical components (stages of building out data warehouses, etc.) and onboarding analytics talent (hiring those elusive data scientists). Those are great, but I like to encourage credit unions to also consider their business focus — and give just as much or more thought to what analytics work will be the organization priority, with what expectations accordingly.

    I hope that provides some useful guidance.

    Dale Davaz
    STCU R&D Strategist
    CULytics Community Chair

    • CU Employee CULytics Founder

      Thanks for sharing Dale.

      I typically see data strategy to have 3 main areas. People Focus, Process Focus and Technology Focus.

      People focus has details around aligning with various execs and team in the organization and boiling them down to common roadmap of objectives and challenges. And then having constant alignment with them.

      Process focus has details around alignment, requirements gathering, design, development and delivery of the data solutions

      Technology focus brings forth the decisioning around what tools and technology to use to drive the data journey maturity.


  • CU Employee CULytics Founder

    Hi Kurt,

    I shared First Tech's journey at 2016 Summit. Check it out here -

    Let me know if you need any help with your strategy/planning roadmap.



This reply was deleted.