Over the past decade, the tech industry has been talking a lot about big data, AI, machine learning and so on. Major players like Google, IBM and Microsoft have been investing billions into developing supercomputers that can crunch the enormous amounts of data they have been gathering from all of us, hoping to provide them with insights on our behaviour that will give them the edge over their competitors. These activities were even given a new name: “Big Data” – the ability to spot almost infinitely subtle patterns in large data sets. The problem was, human beings were not able to develop the algorithms needed to efficiently analyse such data, and so a second technology was developed alongside it: “AI”. This AI was not that of science fiction, intelligent robots and doomsday scenarios, but the simple ability of algorithms to self-learn. It allowed these big data sets to be “interpreted” by computers and to spot patterns, even where the original programmers were not looking.
The world has been living with the consequences of such technology for years now – we all know why we see those particular adverts on Google and Facebook. But as we embark on a new decade, these technologies are becoming available to smaller players – such as the business world.
Over the next few years, the kind of insights previously available only to the Silicon Valley super-giants will become routinely available to businesses and organisations around the world – and digital platforms such as SMLWRLD will be the tools to deliver them. These tools already have access to the right kind of usage data from employees. A successful digital portal with a well-engaged user base is able to capture invaluable information about real-world staff members. The difference now is that the Big Data and AI technologies are becoming available to these tools.
Finally the business world can benefit from the same insights that, as consumers, we have all become so used to being on the receiving end of. So what kind of insights might we look forward to with this new technology?
Not such a foreign concept, but the likes of Twitter have been using AI to analyse conversations for years. Very few internal business tools have been able to do the same – until now. Built-in AI technology can analyse on-site interactions – comments, replies, article posts, article views, article likes – and begin to intelligently interpret which topics and themes are causing the most interest within the organisation. These topics can be conveniently displayed on the homepage, or via executive dashboards, providing major real-time insights into the “mood” of the organisation.
If you add to this deep integrations with the likes of Teams and Sharepoint, the SMLWRLD Platform AI can include interactions from these sources too, allowing for an even richer picture of the “Corporate Conversation”.
As well as explicitly identifying conversations about dissatisfied employees, the portals of the future will be able to infer more subtle behavioural insights from employee interactions. For example, a surge in interest in the Termination Policy document, or increased searches about the Employee Assistance Program.
All would lead the AI to suspect that some negative sentiments are setting in – invaluable insights for managers to follow up on.
In addition, part of the daily usage of the Portal can include “Pulse Surveys”, such as:
- How are you feeling today? (on a scale of sad face to happy face)
- How would you rate the success of your last team meeting (on a scale of 1 – 10)
Such surveys take only a second to respond to, but can be strategically placed throughout user journeys in the site, in order to give an even richer insight into the mental state of users.
Although user engagement dashboards and reports have been around for years, the new breed of Big Data and AI technologies allow these tools to step up to the next level, providing even deeper insights into the areas and parts of each portal that are generating excellent engagement, and those that need improvement.
With such technologies becoming commonplace in the business world, it is natural to be concerned about “big brother” – after all we know that big tech targets us on an individual basis all the time. However, in these types of applications this kind of big data is aggregated to such an extent that it is completely anonymous, and there is no danger of individuals being identified; these are macro-trends and large-scale behavioural insights only.
All this data can tell you a story – a story about what your workforce need and what they are feeling. This sort of information is gold dust to you, and when you respond to it by taking action, it can transform their experience. And that’s priceless.