Frank posted some great comments on Here’s how to get started with decision management the other day and made me think about this, often very severe, problem. As Frank put it:
How do you overcome the moral fear some organizations have when they realize 40-80 percent performance improvements come at 40-60 percent less personnel; so if operational budgets and manager salaries are dependent on the number of subordinate employees, then it is in the best interest for some to resist EDM; especially in state public health organization.
This is a real problem with adopting EDM for sure and one I have seen personally in collections organizations, for instance, where the size of the department is a key measure of the power/success/income of managers. In these kinds of circumstances there really is little chance of success without changing these measures. As in all things, the act of measuring something changes it. Measuring managers on the difference between their spend and their income or output is essential if you are to get them on board with the changes that EDM will bring.
Often it is not worth tackling this kind of problem first. Instead I often recommend that decisions currently not being taken at all or ones that are already being automated poorly be targeted first rather than the replacement of manual decision making. These decisions may not have the bang for the buck that replacing manual decisions do but they help establish that the approach works without having to deal with the whole empire thing.
Frank goes on to make another good point:
Public health activities are driven by funding and politics. A great example is Bio-Terror; there is only one difference between a bio-terror event and any other outbreak or chemical spill – bio-terror is intentional and except for criminal issues, responses are the same: quarantine, clean up, etc.; but states get lots of additional money for bio-terror and create whole sub-organizations with their own information systems…all existing to collect their OWN specific data and report those data by their OWN standards (if such standards exist at all). [It] may be impossible to introduce EDM in these organizations since information sharing is loss of power
Here the problem is not just one of empire size but of the number of little empires involved and the threat to those silos of information sharing. Tackling this problem is also beyond the scope of introducing EDM but it need not be tackled first. While shared information is clearly more useful and more likely to result in better decisions and analytics, it is not essential. Plenty of effective decision management solutions do not use cross-silo data. Indeed connecting decisions across silos is one of the later stages of adopting EDM. The “E” is not meant to imply a need to do enterprise-wide decision management so much as to imply enterprise ownership of decisions – making them explicit (Explicit Decision Management). So the decisions within each silo can be attacked using EDM and can show good results, even if some decisions would require integration of the silos.
EDM is a great approach but it needs the same kind of organizational readiness and flexibility that any new development approach does and it can be limited by the politics and performance measurement systems that are in place. You can, and should, “think global, act local” and get started with a focused EDM project because success will make the necessary organizational change easier.
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Thank you James, this helps a lot. Indeed, this was the approach I took at the public health dept. where I was a contractor assigned to design and manage an EDM project. The system, by itself, does not overcome the “silo” problem completely, but having a single source of millions of dimension integrated, individual records gets about 2,000 online users a day and saves the state over $400,000.00 a year in information access and data management costs. Local (county) users are able to target specific populations and geographic areas to prevent diseases from asthma to STD’s, reduce human suffering and costs to health system.
Frank H. Millard
Policy Analyst, Data Miner, Population Segmentaion Analyst and Predictive Health Modeler — Contractor/Consultant
678-570-7510 (M)