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The Human Factor in Analytics Success

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Intermountain Healthcare has embraced analytics to improve operations, achieve better health care outcomes and make a difference in patients’ lives. The company’s approach to implementing analytics throughout its organization demonstrates a critical lesson: the secret to success is not technical prowess; it’s the human element. Fresh insights don’t matter if you can’t use them to influence people’s behavior.

Many organizations have reached a point where their capabilities to deliver analytics outputs exceed their abilities to consume that information. They have built capacity for analytics production — the technical capabilities that include advanced analytics and data science expertise, technology tools, data management practices and infrastructure. But they often lack the analytics consumption capability that enables the organization and individuals to use data to change a business process or decision, gain business value and move the enterprise forward.

Leaders acknowledge this disconnect. In a survey of 270 senior executives by EY and London-based research company Nimbus Ninety, 81% of respondents agreed that data should be at the heart of decision-making. But only 31% said they had significantly restructured their operations to incorporate analytics, an indication that many still have a siloed approach to analytics that limits its value.i

By focusing on the human dimension of analytics, Intermountain Healthcare connects analytics production and consumption. A closer look at Intermountain’s culture, strategy and approach reveals how the company creates value and is set up for continued success.

Organizational Alignment

Success with analytics requires an organizational commitment to make productive use of data integral to the business strategy. Having instituted the use of statistical analysis decades ago, Intermountain’s leaders fundamentally see analytics as a key element of how they create value. The company demonstrates this organizational alignment in three ways:

Strong leadership and culture

Intermountain has built an analytics-steeped culture that permeates every level, starting at the top. In 1986, the company hired Brent James, a medical doctor with a master’s degree in statistics, to champion quality improvement principles and initiatives and to send a strong signal throughout the organization about the importance of using data to deliver results.

Intermountain also fosters an environment in which any employee can make formal or informal requests for analytics support. Encouraging employees to ask questions—What does the data say about this certain treatment? What insights can I glean from this result?—has a positive, lasting impact.

Organizational structure and teaming

In every business, there is a discussion about how to organize resources and where to position analytics expertise. Intermountain made a conscious choice to place its analytics teams close to frontline business users. Most of its Clinical Programs have their own data teams; members include a data manager to ensure proper data collection, a data analyst to flag important trends and a data architect who assembles data from various sources inside and outside Intermountain. As a result, data and analytics experts are very close to business problems and to how data can be used to address them.

Systems and repeatable processes

Intermountain embedded analytics into business processes to create learning loops. Dozens of different data-based decision support tools, also known as care process models, help employees care for patients. Cardiology is a great example. Every time doctors treat a heart attack victim, data on the operation is shared with the treatment team within a few days as part of a rapid improvement process. This feedback helped reduce the median “door to balloon” time to 57 minutes, down from 90 minutes. Intermountain’s consistent, repeatable processes deliver these results.

Individual Alignment

Strong leadership, as well as the right organizational and business processes enable a company to leverage analytics. These conditions align analytics programs with organizational strategy. Successful execution still requires individuals to act. In the case of Intermountain, three factors give employees the best chance to leverage analytics for positive impact:

Decision biases engaged constructively

Intermountain recognized up front that everyone receives new information with a personal frame of reference, and then built a culture of engagement into its analytics work. For example, a number of surgeons believed that their preferred surgical devices (coronary sutures) yielded superior results. When shown analytics data that indicated more expensive sutures yielded no appreciable difference in patient outcomes, most of the surgeons switched. Notably, Intermountain did not force those who disagreed to follow suit; such an approach builds loyalty to analytics processes and avoids engendering staff resistance.

Capabilities built through hands-on training

Often when organizations talk about adding analytics capability, they are referring to analytics practitioners themselves. But capability building also happens on the front lines. Thinking through the types of learning experiences and development opportunities employees need to consume new insights is an important part of creating a data-oriented culture. At Intermountain, that meant improving doctors’ knowledge of the data and analytics processes and tackling user resistance head on.

Incentives that drive people’s behavior

Intermountain is not waiting for the industry to fully embrace value-based health care. A new insurance product in 2016 will make physicians and Intermountain jointly responsible for health care costs. Doctors who reduce costs will earn more income, and the company thinks this incentive will help them focus on data-driven decision-making. How an organization measures and rewards employee performance matters, and Intermountain’s approach shows the importance of aligning incentives with desired behaviors.

An organization can have the best technology, the best analytics and the best insights—and still not create any business value. It typically takes a human being to change a business decision or process using the insights that analytics can provide. As Intermountain Healthcare demonstrates, the commitment to the human dimension is driving return on analytics investments.

References

i. Ernst & Young LLP. “Becoming an analytics-driven organization to create value: a report in collaboration with Nimbus Ninety.” 2015. http://goo.gl/kQLz7O.