As an aside, first a lesson from decision theory which the Horizon programme drew on from the planning of the manned mission to Mars (and perhaps more importantly the return journey). Faced with a gigantic range of Big Data and the need to make complex decisions, a simple principle, transferable to procurement, was used, namely, focus first on identifying those decisions which narrow down most options, they, in turn, cut out the need to consider many of decisions which would only have been relevant to the eliminated options. Simple principle but sometimes overlooked.
However, back to the core point. I began to think of the potential of Big Data for procurement decision making. Most recognise that spend analytics provide a core foundation for procurement improvement but I think that is now Level 1. If we were to capture a wider range of data, mine it and uncover patterns, we could:
- Predict the demand/level of consumption of a good/service and help profile demand;
- Predict the optimum supplier capability and capacity required to deliver a required outcome in a given situation, and therefore reduce paying for over-capacity;
- Identify the costs which could be removed to deliver a given solution;
- Predict supplier behaviour and their likely negotiating responses;
- Predict the optimum form of contract pricing, for example, fixed price, rise and fall, index linked;
- Predict the optimum contract term;
- Predict the most advantageous time to 'go to market';
- Predict the optimum period required to solicit the best bid;
- Predict the optimum budget and whole life costs;
- Identify the key areas to focus on in contract management;
- Predict procurement risk profiles and optimum mitigation strategies;
We now need to shift our thinking about Big Data from 'what if?' to 'why not?'.