Separability and the Demise of DSS (Decision Support System)

The evolution of any phenomenon is an interesting story. Some follow a linear path which we admire while some follow a non-linear trajectory which fascinates us. Both continuity and discontinuity are legitimate objects of attention and study, and I don’t see any point in inflating one against the other. In some cases, some dimensions account for either continuity or discontinuity. The key point to grasp is that every ‘discontinuity’ or ‘break’ introduces a new (series of) continuity. Every break in pattern creates another pattern, even if for a short while. Technical analysts tracking currencies and securities are well acquainted with these phenomena.

To come back to what I wish to argue. In the business of software, the dimension of separability has stood out as a leading dimension that explains the path it has followed.

The beginnings of software as an industry or the business of software is traceable to the time when software was separated from the hardware and made an independently saleable product – Microsoft’s operating system which became an independently saleable product, which, until then, was bundled into the hardware. This is shown, along with other insights, by Michael Kusumano’s ‘The Business of Software’, a fine book to read. Since then, separability has been central to the growth of the business of software. Slowly during the initial stages and rapidly as reliance on information technology gathered momentum, software which were part of a whole system (ERP) got separated and then built as a separate business.

The first major milestone in this was CRM (customer relationship management) from Siebel. Given that this happened during the dotcom boom, it acquired a visibility that opened up doors for many other highly focused software products such as procurement software, vendor management, supplier management and so on. It didn’t strike anyone to ask if the basic business software system they were using was itself capable of analyzing data to reveal the intelligence buried within.

There have been many since then but arguably the most intriguing development in this is the growth of what has come to be called ‘analytics’ or ‘data science’ together with ‘big data’. What is galling about this development and the debate it has unleashed is that it seems as if the world of business has just begun using information or data to arrive at decisions. People seem oblivious of what is possible with good old Excel or business intelligence software, which had become a big business by the first decade of the 21^st century and all the leading global software companies had a product. However, even as customers were getting accustomed to using this software, the cry for analytics gathered rapid momentum and within a short time gave birth to a ‘new discipline’ – data science. A corollary from this is that the potential of any software has perhaps been never fully utilized, as the IT industry takes its customers (whose understanding of technology is several notches lower, except in very recent times) ‘to the next level’.

This is so bizarre because, almost since the beginning of business application software, analytical capabilities were inherent in the software system, be it ERP or Accounting, be it vendor analysis, procurement analysis or what have you. As long as the business software captured data (through recording of transactions), analytical capabilities came integral within it. It was then called DSS – Decision Support System. Not long ago, a fair number of people connected to the IT industry would have known the meaning of DSS. We are talking of just 10-15 years ago. However, it is doubtful if people today, outside a miniscule minority, will even be aware of the acronym. Accounting packages came with DSS as a matter of routine and was a crucial aspect in a positive evaluation. In fact, in general, the quality of a software package was assessed on the basis of the quality of its DSS, which helped managers (at all levels) analyse relevant information to derive the intelligence that would form the basis of decisions.

Today, analysis has become a separate software and function. There is a whole new body of people who take on the responsibility of analysis. We are told, by the global business and technology media, that there will be a huge shortage of ‘analytics professionals’ within the next few years. And even within this ‘analytics’, there is further separation and segregation of functions into ‘social media analytics’ ‘white noise analytics’ and so on. In fact, shrewd markets simply add the word ‘analytics’ to any preceding word to lend visibility. Now many major and minor universities offer Masters in ‘Business Analytics’ or ‘Big data analytics’ or just ‘Analytics’ or ‘Data Science’. The demand for such courses has been growing in the last five years. The most annoying aspect of the high decibel level of the current marketing of ‘analytics’ is that it creates the misleading impression that earlier decisions were not based on information or analysed data. That’s progress for you!

Takeaways

Analysis of information was part of core of any software, in the early stages of information

Systems

Evolution of software is a story of creating separate branches for analysis

The growth of the business also underlines enormous waste