Research
suggests 40% of major business decisions are based not on facts, but on the
manager’s gut.[1] Most
of those gut-based decisions are not life-endangering. However, many of them
can directly impact the organization’s viability.
In
Workers’ Compensation, critical decisions are made not only by managers, but by
front-line workers. Claims adjusters make course-swerving decisions every day. How
accurate and timely are the decisions they make? What about the decisions made
to ignore information and avoid taking action?
How
are outcomes traced back to the decisions made and not made? What
accountability is built into the process? What kind of decision support is
available? Are any of the decisions based on objective data?
Business intelligence
Business
intelligence, derived from analytics (data analysis) can inform business
decisions throughout the organization. More importantly, the analytics must be
infused into operations to lead to action. Only analytics that are linked to
operations can consistently and positively provide decision support that create
positive outcomes.
“If you really want
to put analytics to work in an enterprise, you need to make them an integral
part of everyday business decisions and business processes—the methods by which
work gets done and value gets created.”[2]
Sequestered knowledge
Both
garden variety analytics and highly sophisticated predictive modeling are
common now in many organizations. But few apply the analytics to their
operational process effectively to make a significant impact on outcomes and
profitability. Unfortunately, the best practice exceptions are not often found in
Workers’ Compensation. Applied analytics in Workers’ Compensation, and
particularly those relating to the medical aspect of claims, is rare.
In
Workers’ Compensation, analytics are most often sequestered in the executive
suite. Analytic results are shared at board meetings and are lavishly portrayed
at marketing shindigs or annual reports. They are represented in colorful
graphics while decision-makers ponder their meaning. Nevertheless, just executing
and reviewing analytics has little impact on decisions made by middle managers
and front line workers.
Analytics must be linked
to operations to make them actionable.
Dashboards are not
actionable
Dashboards
have become a fashionable way to display analytic results, but they don’t link
the analytics to operations. They do not change behavior. They are designed to
portray conditions in the organization across a broad swath of indicators in
one view.
An
example is a hospital where a dashboard displays vital operational statistics including
admissions and discharges for the period, average lengths of stay, and acuity
rates. Dashboards are interesting and informative of business activity. The
remaining question is, who should do what to incorporate the knowledge? What
should be done operationally to effect the indicators going forward?
Basically,
dashboards are for viewing only, and unless the organization has designed response
procedures for assigned persons, the impact is negligible. Dashboards have no direct
relationship with operations and no mechanism for tracking responses to the
information. Changes in process are anecdotal only.
Corporate
communications, regardless of how sophisticated, do not effectively translate
analytic knowledge into action on the front line.
Actionable analytics
For
analytics to be actionable they must be linked to, and fused into operations automatically.
Front line workers must be led by the information process to take
appropriate action.
The
best way to do this in Workers’ Compensation is to electronically monitor the
data, execute the analytics in real time, and initiate the desired actions
among workers by means of an automated electronic message. This approach
hurdles the communication log jam found with immediate, specific information
sent directly to the person who can best act on it.
Infusing
analytics into operations requires a computerized system specifically designed
to monitor and analyze all transactions and to automatically send alerts,
thereby communicating the results of current analytics to the appropriate
persons.
Accountability
When
the computer system identifies a high risk situation in a claim, the
appropriate person is automatically notified electronically. At the same time,
the system should also keep an audit trail noting all claims identified, the
reason, and to whom the alert was sent. The end-to-end process will infuse
analytics into the process, render the process more efficient, and establish
accountability.
When
a person is alerted of a high risk claim, action is expected. Some
organizations have formal procedures for the actions required under a specific
set of circumstances. Such actions are documented so that outcomes can be
traced back to the claim conditions, initiatives taken, and the persons
involved. The results are exponentially improved while the data gathered in the
process enhances organizational performance intelligence.
Results
Analytics
by themselves cannot and will not change outcomes. But analytics linked to
operations through specifically designed systems will effect both the process
and outcome. Only actionable analytics create value.
Karen Wolfe is the
founder and president of MedMetrics®, LLC,
an Internet-based Workers’ Compensation analytics company. MedMetrics offers online
medical management apps that link analytics to operations, thereby making them
actionable. karenwolfe@medmetrics.org
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