James Taylor's Decision Management

Kyle McNamara responded to a post of mine about analytics and how confusing it is as a word with one of this own What is Analytics?. Kyle had a nice definition that focused on competitive advantage and predicting outcomes and used a graphic from Competing on Analytics which I too find useful. The most useful thing was last, a graphic with an illustration of the use of analytics across the value chain.
Looking at this, however, it seems to me that few of the examples are the kind of operational decisions on which I focus. Here, then, are some additions by area of value chain:

• R&D
  This is one without much in the way of operational decision making
• Production
  Optimizing supply chain decisions is one but others like production scheduling and process control often require operational decision automation and analytics.
• Marketing and Sales
  One of the classic areas for operational decision making, optimal pricing and targeted/personalized offers are both operational decisions that use analytics. More generally a Best Next Offer or Next Best Action approach to sales/marketing/support requires strong analytics in operational decision making
• Distribution
  Route optimization is one if it is done dynamically. As RFID becomes more widespread, real-time decision making using the RFID information will become more important too as I noted here.
• Customer Service
  Kyle gets started with personalization but retention offers to specific customers as well as determining if a particular claim (warranty or otherwise) is valid require other complex operational decisions.
• Finance
  Not so many here but fraud detection as well as compliance with things like anti-money laundering decisions might go here.
• HR
  Very large organizations might automate decisions like scheduling