Older CIOs will remember the days when the term ‘decision support’ was commonly used in reference to the reporting and analysis capability embedded in IT systems. As all kinds of new fangled ideas then came onto the market, however, carrying much more dynamic labels such as ‘data warehousing’, ‘analytics’ and ‘business intelligence’, the older phrase became unfashionable and ultimately regarded as synonymous with the production of the infamous ‘doorstop report’, containing far more management information than anyone could ever use effectively.
Lately, though, we at Freeform Dynamics have been involved in a number of activities around the management and use of information for business decision making, and when you look at the nature of the challenges faced by organisations today and some of the language used, you sometimes begin to miss the old way of terminology. The trouble is that when people hear the current buzz words and phrases – business intelligence, analytics, data warehousing, and so on – they tend to map the various terms onto technology categories for either the ‘heavy lifting’ extraction, transformation, collation and crunching of data, or the clever analysis that typically follows.
With this in mind, when we then see reports from analysts highlighting business intelligence (BI) as being high on the CIO agenda, it can all get quite misleading. Our own research consistently tells us that many organisations continue to struggle with the problems of data fragmentation, duplication, and so on, and indeed this is increasingly an area for improvement that is recognised and prioritised for investment. But in technology terms this encompasses a whole range of information management and delivery solutions beyond what many would consider ‘classic BI’.
One of the activities the Freeform team has been involved in recently, for example, is writing a short book on the use of information at the edges of the business, which is basically about surfacing the right data at the right level and the right time in a business process. In many cases, this does not involve a lot of ‘analytics’ or ‘BI’ per se, as the data required may actually be quite simple – e.g. an aggregate view of customer activity in a call centre context, or a quick breakdown of the calls hitting the customer services agents in the past hour.
The problem to be solved in this kind of scenario is around systems integration, rules definition, workflow execution, and so on – basically the coming together of information management with domains such as service oriented architecture (SOA) and business process management (BPM). Get this right, though, especially if you can take an architectural approach to information integration and delivery, and you can enable even relatively unskilled workers on the front line to make key decisions, avoiding the overhead and delay of referrals, escalations, and so on.
Beyond the structured process world, a lot of the challenges among professional workers when it comes to getting their hands on the information they require to do their jobs effectively are to do with identifying, locating, extracting and collating both structured and unstructured data from various internal and external sources. That’s not a job for a traditional BI toolset either, that’s about everything from portals, content management and enterprise search, through to collaboration and potentially even social media systems.
Coming back to some of those high level CIO surveys, we suspect that when senior managers are asked about their priorities, and one of the options on the survey form is BI, they take this as proxy for all forms of activity and investments aimed at helping their workforce make better decisions. It’s the old problem of mixing up subjective technology categories with an objective definition of what the organisation is trying to achieve. The misleading view thus comes from the round trip – the researcher asks about BI investments, the CIO translates this to spend on helping people make better decisions in general, and the analyst interprets the response as referring to budget allocated to the BI solutions product category (however that is defined) – either that, or there are going to be some very surprised and happy BI sales guys out there.
Returning to where we started, it would actually be quite useful to reinstate the term ‘decision support’, as this encapsulates the problem definition very nicely. Sadly, it’s probably got too much baggage to be resurrected, however, so in the meantime, let’s all at least remember its spirit. Enabling effective decision making is not always about the clever number crunching end of the spectrum. In both an operational and professional worker context, huge benefits can often be gained from implementing far less glamorous capability.
While traditional business intelligence continues to evolve into areas of predictive analytics, in-memory databases, and other sexy technology, which are all potentially very important and valuable, it would be a mistake to assume that the solution to all ‘decision support’ problems lies there. It’s therefore worth taking a look at the amount of time wasted on the front line of the business, and the risks that arise from a simple lack of basic information access. The chances are that there is some low hanging fruit just there for the taking.