The previous post noted that vendor worldviews change and can do so with more speed than product and service offerings. In doing so it made the distinction between worldview and product. Products solve problems. Problem solving requires problem diagnosis, which requires a worldview. Products require disciplined and painstaking development, which takes time. Worldviews, on the other hand, can be far more adaptive.
I’ll illustrate this through a quick look back at Cognos’ evolving worldview over the past five years. By way of personal disclosure I worked at Cognos from mid 2003 to the end of 2005.
In late 2006 Cognos remained positioned as a leading business intelligence provider. As this December 2006 press release illustrates the term “analytics” was starting to attract mainstream attention (unsurprisingly: 2006 was the year of Tom Davenport’s seminal Competing on Analytics HBR paper). Clearly, however, Cognos is still presenting itself as squarely in the business intelligence camp.
Cognos announced its acquisition of Applix a year later, at which point its positioning began to shift. Applix’s flagship product, TM1, begins to be presented as an enhancement of Cognos’ “analytics capabilities”. See, for example, this press release from December 2007. TM1′s strength and reputation, then as now, was in planning, budgeting and reporting. Cognos already had Cognos Planning for planning and budgeting and Cognos 8 for reporting. To this point Cognos had used “analysis” as a synonym for OLAP (also a Cognos 8 capability, previously PowerPlay). The term “analytics” is new and becomes duly associated with the new acquisition, TM1. Note that the functional capabilities have not changed substantively – the acquisition has doubled them up – but the worldview has expanded in response to the increasing buzz around “analytics”.
The “analytics” talk continued following IBM’s acquisition of Cognos another year later. This IBM press release from October 2008 associates the Cognos product stack, now including TM1, with both “analytics” and “advanced analytics”. It also associates enterprise search technology with “text analytics”.
IBM’s subsequent purchase of SPSS – in mid 2009 – incorporated a set of products more conventionally recognised as “analytics”. The acquisition press release positions these as “advanced analytic” and “predictive analytics” capabilities.
There are two trajectories here: language and product. The change in language (the integration of various flavours of “analytics” into the worldview) occurs well ahead of any change in product capability (in this case via the TM1, Cognos, and SPSS acquisitions rather than through in-house development). Being largely a linguistic phenomenon, positioning is inherently more flexible than product.
The lesson here for organisations investing in Business Analytics is that the languages through which vendors communicate their worldviews are more like different dialects than a common language. Not only do you have to understand precisely what “analytics” means for your organisation, you also have to understand whether it means, say, OLAP or Predictive Modelling for each of your prospective service providers.
About us
Analyst First is a new approach to analytics, where tools take a far less important place than the people who perform, manage, request and envision analytics, while analytics is seen as a non-repetitive, exploratory and creative process where the outcome is not known at the start, and only a fraction of efforts are expected to result in success. This is in contrast with a common perception of analytics as IT and process.Authors
- Eugene Dubossarsky (43)
- Greg Taylor (4)
- John Lowry (1)
- Richard Fraccaro (1)
- Stephen Samild (87)
- Tapir (1)
Tags in a Cloud
AIPIO analyst first Analyst First Chapters analytics analytics is not IT arms race environments big data business analytics business intelligence cargo cults collective forecasting commodity and open source tools complexity data decision automation decision support educated buyer EMC-greenplum forecasting HBR holy trinity human infrastructure incentives intelligence model of analytics investing in data lean startup literacy management culture MBAnalytics operational analytics organisational-political considerations Philip Russom Philip Tetlock prediction markets presales R Robin Hanson Strategic Analytics tacit data TDWI Tom Davenport uncertainty uneducated buyer vendors why analyst first

