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Antov, Deeken, and Killian return with five more tips on how health companies can catch up to other industries in their use of analytics for business.
In our previous article, we described five high impact areas for advanced data analytics in your healthcare marketing organization. The potential value ranges from broad strategic planning issues to evidence generation for promotional claims (in particular, claims and studies with respect to utilization, costs, power consumption, etc. as opposed to clinical claims that would be reflected in a product’s Indications For Use). But how to go about it? Like any new initiative, the value potential also carries investment risks. Here, then, are five recommendations for building data-driven approaches into your business:
Establish a Champion
Consider appointing a Chief Data Officer, even if only a temporary responsibility. This person needs to have a holistic view of the business, from marketing to finance to IT, and should be responsible for creating and driving long-term strategies and investments. Alternatively, some organizations have favored a co-chairmanship arrangement, with an IT/IS lead joined by a representative of the internal end-users (e.g. Marketing). However you address the question of leadership, remember that it’s no more fair to ask your IT department to create a solution on their own than it is to have your engineers create new products without the voice of the customer.
Allow Flexibility Early On
Be hypothesis-driven while allowing time to experiment. Start with small pilot projects and simple analyses from which the organization can learn. While the team should be thorough and detailed in planning and anticipating the ways in which the data will be used, be open to the possibility that the most valuable contributions may be down the road, in ways not originally anticipated. In the early stages, allow for some compromises, such as using periodic “snapshots” of data rather than making the full investment in enabling real-time data streams. The reality is that the organization will have to be adaptive as to how it uses data to inform decision-making, particularly at the onset. It is imperative to apply flexibility in the design and operations of your analytics frameworks to ensure necessary and appropriate consumer insights and implications are being drawn. Also, consider working with smaller vendors or contractors that can provide quick-win capabilities with relatively low overhead, and who can help educate your team on the key issues as they go.
Start a Running Wishlist
When Terry McFadden set out to “solve” big data for P&G, he asked managers and analysts, “Imagine you had a magic 8-ball and you could ask it anything, what are the wicked problems you wish it would answer?” That may be a difficult question to answer off-the-cuff, but consider if your teams maintained a running list of complex “1-off” analyses they prepared over the course of a quarter. Keeping track of those various efforts, along with the various processes and pains that went with them, will help form a solid foundation of what can be streamlined in the future.
Expect Big Decisions Later
Once early stages have yielded positive results and helped to expand buy-in, prepare for challenging discussions and decisions as the effort scales more broadly. Peter Daw, currently VP of Strategy for Fortune Brands and former Global Head of Analytics for Mondelēz International, says to expect extensive discussions around issues like data hierarchies, structure, and definition. “There were issues on which we needed to spend lots of time, such as the definition of a ‘brand’ vs. a ‘sub-brand,’ for instance. To enable managers to drill down to the level of detail they needed on a global basis, you may end up with hierarchies that have eight or more levels.”
Envision New Data Streams
It’s important to get products connected in one way or another, to open up new sources of information to you and your customers. Start by requiring new product development efforts to address connectivity questions as part in the early definition stages. Should sensors be added to mobile equipment? Can stationary equipment be connected to the hospital network? For smaller products, what can be done to make them compatible with various asset-tracking technologies that hospitals and clinics are already adopting? Is there data that we can collect that could itself be a saleable item or service feature?
A useful exercise at the beginning of any such effort is the documentation of both existing data and notable data gaps. We find that oftentimes companies do not fully utilize (and thus maximize) the internal data sources to the fullest extent possible. For example, working to extract the maximum value from the transactional and behavioral data already collected on customers will go a far way in sorting through data complexities and hierarchies.
Whatever path your organization takes, be confident in the knowledge that, though there may be challenges and wrong turns in the early stages, the overall trend is here to stay. Products and services across the full spectrum of healthcare delivery are becoming more “digitally” sophisticated. It is crucial that you make the investments now to stay relevant in the future.
About the authors:Dimitar Antov, Peter Killian and Jason Deeken are colleagues at The Cambridge Group, a Demand-Strategy consultancy firm based in Chicago celebrating more than 40 years of client impact. Jason Deeken is a healthcare executive with more than 15 years’ experience focused on strategic issues and product development, having worked as VP of Sales, Senior Director and Director/Manager at Western, Steris and GE. Dimitar and Peter are both Principals at The Cambridge Group, with 20+ years between them bringing the latest in data analytics and techniques to a range of clients in CPG, Retail and Healthcare sectors.