Sometimes catastrophic events cannot be anticipated and the best an organisation can do is be prepared. The explosion at the Buncefield fuel depot in Hemel Hempstead last December shows how a disaster can strike unexpectedly and highlights the importance of preparedness.
But are organisations doing all that they can to identify developing problems?
For several years now, businesses large and small have been applying sophisticated techniques to look for patterns that indicate certain behaviours. To date, the focus has been primarily on trying to understand customers' propensity to buy certain goods and services, to determine who future customers might be, or to look for potentially fraudulent behaviour.
To do this, organisations have been applying business intelligence tools to the vast volumes of data captured by their underlying business systems. Moore's Law has meant that the computing power necessary to find the metaphorical needles in the haystack is available for minimal investment. The continual development of business intelligence tools has allowed the analysis to be undertaken from the desktop by knowledgeable users, with little need for deep technology skills.
Could such tools and approaches be used to identify patterns in non-customer or non-financial data? Could they show patterns of behaviour that may identify cultural or process issues which, if addressed, could reduce the likelihood of a future major incident?
Some businesses clearly think so. At least one major oil and gas company has applied business intelligence techniques to look for patterns of behaviour in its health and safety data. So why is it not more widespread?
To date, business intelligence has been applied most prominently in the finance and marketing functions of an organisation. The data underlying these business areas is awash with numerical facts that business intelligence aficionados love to get stuck in to. Using business intelligence on data which is intrinsically non-numerical in business areas such as health and safety simply hasn't been the norm. But there is no reason why this needs to continue.
There is no doubt the underlying data exists. In the construction, chemical and energy industries, to name but a few, there are copious regulations covering everything from monitoring toxic substances and "spillages", to compensation and response regimes following incidents.
In the UK, for example, the Integrated Pollution Prevention and Control (IPPC) regulations and Control of Major Accident Hazard (Comah) regulations 1999 place a significant burden on companies to gather data and closely monitor their operations. And it does not end with national regulations - for many large organisations, they must also meet a whole raft of international regulatory obligations.
In response to these regulatory burdens, large companies have invested heavily in information gathering systems to ensure their compliance. But the emphasis of these investments has been on managing day-to-day operations and discharging compliance obligations. What some are beginning to realise is that the data generated by these systems can provide insight way beyond the original intent.
Through the application of business intelligence techniques, informative patterns of behaviour can be identified, such as sites that deviate from the norm in terms of elapsed time from incident to resolution. Or individuals who consistently sign off large groups of incidents together, perhaps indicating an attitude of doing just enough to be compliant rather than a genuine interest in diligent behaviour.
Identifying and acting on such patterns clearly has a significant role to play in preventing future incidents. Often, a sequence of apparently trivial events can lead to a significant incident, and the old adage about looking after the pennies very much applies.
Clearly, the effectiveness of any such exercise depends on the type and quality of data that is captured and the analysis applied to it. In this regard, organisations will encounter all the same issues that a traditional business intelligence project does.
Key amongst these will be getting clean, consistent data from all the underlying business systems. A particular issue is areas where, unlike financial information for example, there are not usually business process steps aimed entirely at ensuring accurate data. As with the analysis, business intelligence approaches to data management will be key to a successful solution.
Business intelligence is not a silver bullet, however. While it is an excellent approach for bringing data together and providing powerful analysis and reporting capabilities, it must be accompanied by significant cultural changes. Many oil companies, for example, are now seeing health, safety, security and environment (HSSE) issues as central to their continued success and putting them at the heart of their culture.
The application of business intelligence approaches in this important area can, however, deliver significant benefit. It enables organisations to re-purpose the valuable data they gather from operational systems for compliance, and improve their HSSE practices and, indeed, improve their business.
There are parallels in other industries such as financial services, for example, where companies have been able to mitigate the cost of regulatory compliance by re-using data for business process improvements and generally upgrading corporate governance regimes. Business intelligence tools play a valuable part in enabling this.
This does not mean, of course, that incidents such as Buncefield will not happen in the future. But it is just possible that equally devastating events might be prevented. Unfortunately, we never know what we manage to prevent.
Mark Douglas is director, and Nathan Jones is senior manager in consulting at Deloitte