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Our Methodology

From Ideas to Implementation

Some firms focus on delivering lengthy strategic reports, leaving you with the hard work of figuring out how to implement them.

Some firms focus on implementing tightly defined solutions, leaving you with the challenge of connecting initiatives to strategy and building forward-looking momentum.

Our analytics approach is different.

Our seasoned teams have the ability to start from strategic ideation and carry the work all the way through to adopted implementation. This ensures that our clients actually generate return on their investment and focus on those initiatives that will generate the most value and momentum.

1. Engage Leadership

Elder Research leaders work closely with executive teams to tie data and analytics strategy to their corporate goals. We concentrate on prioritization, investment planning, measuring return, change management, and data literacy training.

2. Design & Deploy Solutions

Our data science and engineering teams work closely with your team to ideate, design, develop, and deploy analytic and machine learning models into production environments. We work in an agile “test and learn” fashion to maximize transparency, velocity, customer engagement, and solution adoption and buy-in.

3. Grow & Mature Data Value

Our leaders and engineering teams work closely with your team to drive and grow data value across your organization. We don’t build data lakes for their own sake, but establish data and analytics architecture and infrastructure to enhance data’s value, movement, and use across the organization.

A Holistic Approach

These steps require more than analytical skill. In fact, the analytic part of the process is often straightforward compared to the vital surrounding steps of defining the opportunity, collecting data, and successfully delivering the results to a decision maker or automated system.

To bring a solution from idea to implementation usually requires a team with varied experience, a shared goal, diverse skills and perspectives, and a healthy dose of curiosity. The sometimes-arduous process is not formulaic, but requires depth of insight, creativity, and flexibility. Ultimately, a healthy balance of data and people skills critical.

The punchline? Analytic success requires a holistic approach and a “Data-Driven, People-Centered” mentality.

Want to get more value from your data?

Let's chat.

Additional Resources

Delivering a Model vs. Delivering Change | Podcast

Why Data Literacy in the
C-Suite Matters | Blog

Leading a Data Analytics Initiative | eBook