Big data and contracts
I just read an article by Larry Lapide, “The Promise and Pitfalls of Big Data”. In it, he observes that making effective use of data is nothing new, but the digital age has transformed the volume and speed with which information can be accessed. In this environment, ‘Picking the right data streams is extremely important, since not all data is information. Information supports improved decision-mak- ing, and not all data is useful for that.’
In the world of contract and commercial management, a typical start point is of very little data and almost no information. The extensive work that IACCM undertakes on benchmarks has illustrated just how little information is gathered on a regular or consistent basis. We have lists of the measures that are or can be used, but there is no consistency across organizations in those they select – or indeed, whether they collect data at all.
Among the most common measures are things like expense to revenue ratios, or numbers of contracts handled per employee. These seem to me of little merit, because in isolation they tell us nothing about relative value. Data on things like cycle times has more meaning, so long as there is accompanying analysis of where and how time is spent, allowing deeper analysis and potential for improvement. But all of the easy and most frequently used data tends to relate to efficiency and if I were leading a contracts or commercial group, I would be far more interested in measures of effectiveness. That is the stuff the executives really want to hear about, the information that drives improved business results through enhanced competitiveness.
In this category come measures such as the level of market push-back on terms and conditions, the frequency (and type) of claims or disputes, the percentage of contracts that are performing in accordance with expectations (and reasons why they are not), the sources of actual (versus theoretical) risk and the extent to which classical risk theory actually causes risks to occur. This type of information directly supports decision-making. It influences internal policies and practices; it highlights areas where capabilities are misaligned with market needs; it generates insight into opportunities for cost-saving or revenue improvement.
Ultimately, it seems to me that those who grasp the potential of better data extraction will rise to the top in terms of the value they bring and the influence they exert. Contracts are a little like shale gas – a largely unexploited source of energy. In this case, that energy could be powering a massive improvement in business performance – but it needs someone with enthusiasm and imagination to exploit it.