Make the business case first…
Then worry about end-user design
McKinsey’s Article Re:
Why data culture matters
A recent, well-written article in McKinsey’s Sep 2018 quarterly newsletter articulated the need for companies to cultivate a ‘Data Culture.’ I couldn’t agree more. Plus, this is prescient in light of the need for better hospice analytics. Although I might add a few points to their incredible insights.
Among the points in the article:
- Achieving deep business engagement
- Creating employee pull
- Articulating business needs
I would only point out that these points are essential to the success of any project, let alone a data-centric one.
Who Moved My Ux Cheese?
In addition to the above points, there’s a strong need to recognize the comfort level of end user groups. Tailoring the user experience and training for each one could bring buy-in to levels a generic ‘one-size-fits-most’ won’t achieve.
Among end users, you can always count on these three groups:
- One group that stays in the ‘novice’ camp
- A wide swath of average
- The tech-savvy
App developers have known this for some time: the adoption rate lives and dies by the Ux (user design or user interface). And the default settings will remain exactly that most of the time. Which is why any system’s default mode must optimize for accessibility.
Furthermore, this is so important for early adoption by non-techies that it can be the difference between success and failure. After that, a truly great Ux can offer a ‘peel back the layers’ approach for those who want to dive deeper into data and perform more in-depth hospice analytics.
Democratizing Hospice Analytics
I thought this quote from the CIO of Boeing was particularly insightful:
You have to figure out how to really democratize the data-analytics capability, which means you have to have a platform through which people can easily access data. That helps people to believe in it and to deliver solutions that don’t require an expensive data scientist.
-Ted Colbert, CIO, Boeing
This is exactly why we have embraced PowerBI and Tableu as market leaders in Gartner’s reviews of BI platforms. Also, see Microsoft’s take on Gartner’s research here. These solutions combine powerful back-end data tools with intuitive end-user visualizations. Never before has insight been so readily at hand.
Solve the Most Pressing Questions First
Or as Stephen Covey puts it: begin with the end in mind! And even more importantly, with your needs/wants list in place, prioritize exactly what you want before you commit large resources to any hospice analytics or business intelligence project.
The best advice I have for senior leaders trying to develop and implement a data culture is to stay very true to the business problem: What is it and how can you solve it? If you simply rely on having huge quantities of data in a data lake, you’re kidding yourself. Volume is not a viable data strategy. The most important objective is to find those business problems and then dedicate your data-management efforts toward them. Solving business problems must be a part of your data strategy.
-Rob Casper, chief data officer, JPMorgan Chase (emphasis added)
My experiences with hospices across the country has taught me that a culture that values data values decisiveness.
You can’t make decisions in a vacuum. Data, with the right tools and expertise, breathes life into facts. Ultimately, the right hospice analytics goes beyond just facts and tells stories.
- What is our expected length of stay by Dx compared to the national average?
- What did this patient’s total time on census–visits, meds, care location–look like, visually?
- Based on current admissions and Dx patterns, what can we expect our census to look like in the next 30, 60, 90 days?
Apply some leverage to your data by bringing in outside expertise as your hospice analytics and business intelligence solution.