It will not come as much surprise that recent Quocirca research1 shows most European businesses are reliant on their IT systems to drive commercial transactions. However, measuring a given business’s transactiveness (the degree of this reliance) is a useful gauge for looking deeper in to how IT systems are managed to ensure responsiveness and a good customer experience.
The first observation is that highly transactive businesses are more likely to be using flexible IT platforms; that is, virtualisation and on-demand infrastructure (platform and/or infrastructure as a service – PaaS/IaaS). A second observation is that this goes hand in hand with a recognition that IT operational intelligence has an important role to play, not just in ensuring IT systems are responsive, but that they are reacting to commercial requirements and that all relevant staff have a view of this.
For the purposes of the research, IT operational intelligence was defined as follows: “harnessing machine data to gain real-time insights into operations to access, tune and improve IT and business processes, to identify security threats, highlight performance issues and see emerging customer trends”. To get a measure of the capability that the organisations represented by the respondents had in place, an operational intelligence index (OI-index) was created with a range from 0-3. The index measured the capability organisations had to use such intelligence in the following areas:
- Search and investigate
- Proactive monitoring
- Operational visibility
- Real-time business insights
The more capability they had in each area; the higher the overall OI-index value. Scores varied widely, but went up in line with transactiveness and the use of flexible infrastructure. Those organisations using flexible infrastructure as a primary way of deploying IT had an average OI index over 2, whilst for others it was less than 2. In other words, flexible infrastructure provides the business agility needed by transactive businesses but supporting operational intelligence tools are needed to make it all work.
However, it goes well beyond just having the tools in place; as important is the job roles that get to view the intelligence provided. Most provide some level of insight around operational intelligence to IT managers. However, those with a high OI-index are much more likely to go beyond this and provide a view to other job roles including those at board level. This is because they are using IT operational intelligence to provide real time business insights which is of value across an organisation.
Operational intelligence relies on machine data as its raw material and as with any intelligence, it is only as good as the data gathered. The volumes generate by an organisation’s IT systems can be huge. Over the period of a year, for an average enterprise it can run into billions of data items. This includes things like what data went via which router, who accessed which application and when, the IP addresses, URLs and devices via which web sites are accessed and so on. This makes operational intelligence a big data problem and it fits all the 5 Vs definition of big data well.
These are v for volume as described above; v for variety, covering the range of sources, with their wide variety of formats. If machine data can be used in near real time, it gives v for velocity; and it can add lots of v for value to operational decision making. All of which gets an organisation closer to the truth about what is happening behind the scenes on their IT systems; the last v for veracity. Machine data is what it is; you cannot hide from the facts that analysing it exposes.
That said, much is missed, even those with a maximum OI-index only gather machine data from about 65% of their IT infrastructure; for those with a very low index it is about 15%. Clearly, something is missing to deliver the vision even among the most capable and ambitious and that turns out to be the supporting tools which are often not up to the job.
Mostly, organisations are relying on general purpose business intelligence tools, backed with an assortment of spreadsheets and general purpose databases. Only 27% use purpose built tools; however, those that have implemented specialist tools do gather considerably greater volumes of machine data and will therefore have access to better operational intelligence.
For many it is early days; those with specialist tools in place will extend their use to improve machine data capture the resulting intelligence gathering. The reach of the tools’ use has to include on-demand IT resources as well as those deployed in-house as the most transactive businesses turn more and more to flexible infrastructure to ensure a great user experience and maintain competitive edge.
1 – Quocirca’s report “Masters of Machines” is freely available at the following link http://www.splunk.com/goto/masters_of_machines_whitepaper