One of the common phrases bantered about in the USA’s debate about health care reform involves “bending the cost curve.” The phrase refers to concerns that any legislated solution must address reducing the continual increase of the USA’s health care delivery costs.
What are the issues with “bending the cost curve” for commercial and public sector organizations? One cost reduction approach that has always bothered me is the meat-axe approach of laying off employees…
One of the common phrases bantered about in the USA’s debate about health care reform involves “bending the cost curve.” The phrase refers to concerns that any legislated solution must address reducing the continual increase of the USA’s health care delivery costs.
What are the issues with “bending the cost curve” for commercial and public sector organizations? One cost reduction approach that has always bothered me is the meat-axe approach of laying off employees – sometimes indiscriminately with shave-the-ice-cube percent department job cuts. I previously discussed this in my blog More Spocky, Less Rocky.
Some insights to a better solution might be gained by reading a blog by Purestone Partners consultant Michael Ensley and its subsequent comments. Ensley’s blog is titled Predictive Analytics, Business Intelligence, and Strategy Management. In the blog and discussion Ensley states, “Queries answer questions, analytics creates questions.” IT analyst James Taylor added a comment, “In fact, analytics can answer more questions, more complex questions and more interesting questions. Analytics can raise interesting questions but it has at least as much power to answer them.”
What Ensley and Taylor are discussing are the limitations of business intelligence (BI) and how analytics can enhance BI. Taylor is an advocate of predictive analytics describing its benefit as “turning uncertainty into usable probabilities.” Ensley’s message is that BI and analytics both need a context, typically missing, to know the “priority and purpose” of these tools. He describes this context, for opportunity or problem solving, as best communicated by strategy management (e.g., using strategy maps and scorecard/dashboard performance measures derived from them).
I agree with both of them. Just having lots of data and access to it all is not enough. Analysts and decision makers need additional help on how to more quickly and effectively leverage data, to convert it into meaningful information, and to gain higher certainty that gives greater confidence to take actions.
