Analytics can create value, however, too many organizations fall short of reaping their full benefit. Many analytics users have admitted there is no clear answer when evaluating the impact analytics have had on their business decisions. Demystifying analytics is key for organizational transformation and value creation.
When analytics are applied to the healthcare and life sciences industries, analytics typically focus on clinical, operational, and financial objectives. Popular examples includes how to identify high-risk patient populations in order to improve their outcomes, how to target providers to grow market share, or how to assess the impact an at-risk contract poses to the bottom line.
Whether the objective is clinical, financial, or operational, successful processes begins by engaging teams to identify key business questions to which analytics can provide answers. These questions should be tied to strategy and will lead to better outcomes when answered.
The second habit in Stephen Covey’s book, 7 Habits of Highly Effective People, suggests to “begin with the end in mind”. This is true for analytics. An agile approach starts by asking questions for which you need answers and then assembling the data and analytics which lead to those answers. Questions such as which physicians should be included for targeting based on their patient characteristics and practice patterns and which physicians should be targeted based on their referral preferences may appear similar but ultimately use different data sets. Amassing data merely for the sake of having it may muddy the waters. As an unintended consequence, users may be unsure about what data to use or which approach to take. A company could spend time and money on data that is unable to deliver the needed business insights or the data may be available but not easily accessed.
“Agile” describes not only the development of the analytics but also the upstream process. This type of approach, assembling and validating questions, helps to ensure you are on the correct path. Including cross-functional members, such as end-users, stakeholders, technical experts, and others with different perspectives, helps to round out an understanding of the business problem. Cross-functional collaboration enables the right questions to be asked with the added benefit of getting buy-in from the team. When participants from business development, IT, decision support, finance, and marketing are often in the room together, they often see things from their unique perspectives.
Beginning with questions gradually drives an organization to seek answers rather than data, which over time leads to a commitment to using analytics more effectively. This is a subtle change with a big impact over the long term and will lead to better analytics value creation.
Strategic partnership enables automation of data enhancement for increased return on data investments, 8x faster results, and richer, more granular insights.
Starting with a database of over 310 million patients, we uncovered errors and then developed provable solutions to correct, enhance, and complete the data.