The Growth Channel

Why your strategy team needs data leadership

by Shay Pratt

The data landscape is changing: Not only can you dive deeper into traditional data sources than ever before, but you can also tap into new datasets that improve visibility into consumer preferences, freestanding and physician office activity, and patient journeys across the continuum.

These resources afford great potential; they can enable planning teams to create multi-dimensional market analyses that spark greater confidence in growth planning, improve decision-making speed, and go beyond basic market share measures to better understand the root causes of market performance. 

Tactics for managing the data flood

While more data is a good thing, the rapid availability of new resources poses a big challenge. The data flood prompts strategy and business development teams with questions like:

  • How do we integrate new data into our analytic processes?
  • What new metrics should we use?
  • How do we communicate new insights to (often skeptical) internal stakeholders?

To manage data effectively, strategy teams must focus on three activities:


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1. Ensure sufficient bandwidth. Strategy departments must find the right way to organize their analytics teams for speed and efficiency. Teams that can quickly evaluate new sources of data for their strengths and weaknesses and incorporate them into market development processes may have a competitive advantage over their peers.

But doing so requires investment. We have seen many strategic planning teams with only one FTE dedicated to analytics and data management. Organizations that do not sufficiently invest in analytics resources may not take full advantage of new capabilities.

2. Upskill your team. Strategy departments will need to create new best practices for answering more complex market questions. In addition, emerging business questions require teams to string together insights from multiple data sources to arrive at solid recommendations.

Strategy leaders should embrace more team education to harness new, innovative ways to analyze business questions. Strategy teams may also need to update their job descriptions and hiring profiles.

3. Meet skepticism with effective communication. New data sources mean new metrics: patient share-of-wallet, population share, and propensity scores, to name a few examples. Planners might be well-positioned to navigate these metrics. However, these metrics may be foreign to other stakeholders like CEOs and physicians—who are critical to growth plan decision-making.

To succeed, you'll need a new internal communication playbook that incorporates these metrics while anticipating and neutralizing internal data skepticism.

Introducing the data leadership series

Our research team has prioritized data leadership as a key focus of our agenda this year. This post represents the first in an ongoing series of insights, best practices, and case studies that we will publish to help strategy teams extract insight from emerging data sources:

  • Longitudinal claims data: New, payer-specific data sets provide the ability to map patient journeys across total care episodes, track movement across providers, and analyze share-of-wallet.
  • Government data: Relaxed restrictions on public payer data, including Medicare Part B and Part D utilization and payments, enable more timely access and deeper analytic capabilities for market share and care management.
  • Local market data: A growing number of states offer all-payer claims data sets, not just inpatient utilization, providing improved visibility into the freestanding clinic and physician office landscape.
  • Consumer data: Advanced demographic, retail, and consumer behavior data provide more information on customer needs and preferences.
  • Pricing data: New companies focused on health care pricing transparency promise to generate useful comparative data on providers.

How to be data-driven

Data are everywhere, but can be challenging to harness to improve your performance.

Download our infographic to see the five principles you need to better incorporate data into your everyday work life.

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