Business Intelligence (BI) has long been deployed in enterprise organizations worldwide. A new generation of Business Intelligence software, Self service BI, centered on visualization and user ease has now taken hold in the market. This has opened analytics up to much more of the enterprise than before and relinquishes much of the reliance on IT to produce reports and manage ‘report sprawl’.
Using useful data and insights, “self-service BI” has empowered line of business departments and employees to make business productivity decisions themselves, instead of awaiting the verdict of data scientists and database architects.
Data – A Natural Commodity
Speaking at the 2016 CES Conference in Las Vegas, CEO of IBM Gini Rometty said that: “Data is a Natural Resource.” The 2.5 Quintillion Bytes of data being produced on a daily basis has exponential value to organizations. It is unthinkable to suggest that any organization would not look to find insights and extract value from the data being produced both internally and in the public domain.
Netflix Innovates with Data Driven Insights
Companies like Netflix have dramatically changed the market. Although it is commonly accepted that the increase of bandwidth and streaming capabilities were a huge contributing factor to ‘household brands’ like Blockbuster being displaced, the growth is more attributed to the use of data and the move to producing and distributing their own content. The use of data in the decisions of what content to produce for both Netflix and Amazon have been integral. Sebastian Wernicke in his June 2015 Ted Talk explains how Netflix used big data to understand what content consumers wanted.
How Data Penetrated the Language Barrier
Mark Blyth, the Regional Solutions Manager of a UK based property management firm, told an audience at SoftwareONE’s IBM Watson event in Manchester that Mears Group found countless insights using IBM’s Watson Analytics, not to be confused with IBM’s Jeopardy winning Watson Platform.
One example given by Mark was an insight into engineer visits. Mears Group found that a particular geography in the UK had a high instance of failed visits to residential addresses. When Mears Group ran a report in Watson Analytics, mashing data sets from the local council and Mears, Watson Analytics highlighted that the first language of 77% of the residents in that location was a language other than English. Mears then implemented a policy of sending Engineer appointment letters in multiple languages, resulting in failed visits reducing from 47% to 4%, saving Mears significant time and expense. An insight that admittedly may not have been found without looking at the data sets in this way.
How Self Service Analytics is Changing IT
In Gartner’s July 2016 research paper Targeting New Buyers of IT, analysts discuss how IT purchasing decisions are being made to drive business outcomes from IT rather than technology performance. This paradigm shift is driven by the availability of SaaS solutions having a low or zero touch of IT departments and the need of businesses to seek competitive advantages through the ‘smart’ use of data.
In Coming to Terms with Business Unit IT to Prepare for Digital Business, Gartner insists that:
“The CIO and their team of IT leaders must stop seeing decentralized IT as a threat and recognize that perspective does not help business units leverage the power of new digital technologies or enable the enterprise to learn more widely from these efforts. This will mean that IT organizations must shift from a control strategy to an influence strategy regarding IT and all things technology. For many, it will mean the creation of a holistic business unit IT strategy that recognizes that the value propositions for different technologies require different treatments.”
A shift to generating revenue instead of being a cost center in the business is now becoming the mantra of leading CIO’s and IT Leaders. .
The majority of data that helps deliver insights, in particular around customer experience improvements, is unstructured; but more importantly, the data is outside the organization. Analytics systems with Natural Language Capabilities are likely to be central to moving these kinds of strategies forward.
What solutions should be considered?
Alongside some industry leaders like SAP, Oracle, and IBM, Open Source providers like Hadoop and some of the mid-market players like Tableau, Qlik & Splunk are in the mix, depending on your resources, need, and expertise. There are also very affordable options like Power BI from Microsoft (now available as part of the Office 365 E5 subscription) and Watson Analytics from IBM, both with Natural Language capabilities.
Natural Language capabilities are perhaps what makes these solutions so easy to use because of how easy it is for users to ask a question in natural language, such as; “what is my best selling line this week” and getting an answer back in seconds without having to involve IT. This kind of capability is making this a field that all organizations can take seriously.