Speaking at Codec’s annual Oracle event at the Westin Hotel on November 17, special guest John Hagerty, Vice President for Analytics at Oracle addressed the increasingly important role analytics can play as we enter into the age of big data.
Hagerty begun by stressing the need to redefine what analytics means in the modern business world, that it had advanced to make high level technical or specialist knowledge almost redundant and could now empower businesses towards a new self-service model so that they could have the capability to access, analyse and report on specific data points more quickly and easily.
He added that while a notion of analytics had taken root portraying it as “largely an IT managed service sent out to users in the form of business and reports”, the world of analytics was now undergoing a radical shift. He described this as a new dynamic in how the system, IT resources and business needs interact with one another. Whereas in the past it was a case of IT users having to learn how to decipher the data systems and making do with the limitations of the data provided, today sophisticated reporting tools are able to respond to specific business requirements and user ability levels.
The Value of analytics
The Analytics Imperative, as described by Hagerty, is driven by three elements; insights, actions and outcomes. With advances in artificial intelligence and machine-assisted learning, Hagerty warns that data should not simply be taken at face value as a descriptive reporting mechanism. Rather users should leverage the vast power contained within the new technologies to use the data competitively and to deliver information of real value. If you've got Mozart seated at the piano you don't ask him to play "Itsy Bitsy Spider".
The results of using analytics wisely speak volumes with some organisations reporting a growth of up to 8 times after embracing it as a way of changing and transforming their organisations (not just their reporting processes). And Hagerty argued that such transformations are not a case of reinventing the wheel, rather businesses should “simply leverage information available internally and augment it with info available externally”.
New Age in Data Analytics
We live in the age of data according to Hagerty; users and customer demand data at every moment, they want it personalised to their particular preferences, and they want the data to be smart enough to proactively inform them of any information that is relevant to them.
“Software needs to change to accommodate these new demands” claims Hagerty, and in order to satisfy this demand the new technology enabler that is machine-learning is coming more and more into play.
“It will show up everywhere, performance management, applications, analytics – driving business processes and growth”.
“Largely up to now it has been about a human working with a machine to consolidate data, program, interact and define models. The new way will reverse this relationship to an extent as the machine will explain, recommend and offer contextual insights and self-learning algorithms”.
The Future for Analytics
Explaining new developments in data analytics Hagerty referred to smart visualisation which can make the best recommendation on how the data should be displayed e.g. maps, line charts etc. Think of how much time we waste on decisions that ultimately don’t carry too much value and instead why not let the machines make the best possible choice for you. If you have Netflix you may have already availed of this type of technology, as rather than endlessly scanning through a gigantic catalogue of tv shows and movies the interface will recommend choices to you based on previous viewing activity.
Hagerty also mentioned language processing advances in NLP (Natural Language Processing) and NLG (Natural Language Generation) so that users can talk directly to their data system and use language to request information. The application will respond in kind by adapting to the user rather than forcing them to use pre-configured settings. It can process speech and present visualisations of a specific query and will adapt intuitively to the query itself e.g. display profit margins when a query refers to profitability, and essentially pre-emptively predict requirements. This is known as adaptive intelligence, and often, like the good kid or husband/boyfriend who does the chores without even being asked, the results are welcomed gratefully.
Identifying a key challenge presented by graphical content Hagerty said “Some people say a picture Is worth a thousand words or is it that a picture can generate a thousand interpretations?”. In other words graphs or charts alone will only tell part of the story as the user can misinterpret, misrepresent or simply misunderstand the data. This is something that a development known as natural language generation will seek to address as it aims to combine visualisation and contextual narration as users activate different filters or functions. For example, click on a KPI within a data-set and the system will explain it to you or review attrition rates not just as percentages but based on the type of person, demographic, working hours, salary etc. Such an expanded analysis trail has the ability to provide real insights and inform actionable responses for the benefit of all the business. The changing shift in analytics is summed up by Hagerty as a change in the relationship between the user and agent as he asserts it is “no longer about you driving the analytics engine but what the analytics can tell you”.
Describing this as a potentially revolutionary new technology, Hagerty said it promises to gather people around a common interpretation of data, eliminating confusion and ensuring accuracy and consensus in decision-making. No more rowdy board meetings – let the system do your talking for you“
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