Cloud computing is rapidly becoming an essential component of business transformation. In Kenya, cloud is no longer just a possibility, it is the fundamental tool igniting innovation. At a high level, cloud is an economiser, requiring no massive start-up costs before results can be realised. Cloud is also an enabler: the very best technologies, ready to be put to work to help organisations innovate and differentiate.
But as technology has become essential to the operation of modern business, and complex, organisations such as banks, retailers and many others have found that to be leaders within their chosen fields, they have also had to become exceptional in terms of their understanding and use of technology.
Take banking as an example. A bank’s core purpose is to be the best bank it can possibly be, not to run the best ‘tech-shop’. The thing is, over time, banks have become ever more reliant on technology to enable that purpose.
And as that dependency has grown, so their requirement for staff to manage that technology has grown. This has resulted in the creation of sizeable groups of staff who are dedicated to servicing technology in the back end, rather than servicing customers. But customers don’t choose a bank because it has the best possible back-end technology. They come because it offers the best products combined with the best customer service.
That vision of being the best possible bank might be powered by technology, but it is the technology at the front end that makes the biggest impact in the eyes of the customer – and you can’t invest in front-end systems if most of your resources are devoted to maintaining systems at the back-end.
New wave of technology
Perhaps it is time that we let organisations get back to focusing on what they are best at – be that retailing, banking, or whatever their core mission is – and leave technology to look after itself.
It sounds like a fantasy, but it is the promise made by the newest wave of business technology innovation – autonomous technology. Combining the power of artificial intelligence and machine learning, autonomous technology delivers the capability for IT systems to self-manage, self-repair and self-secure across a wide range of functions and applications.
Let’s take a step back to understand the concept of machine learning. While machine learning itself can be unduly complex, the basic ideas are easy to grasp. Let’s use the example of a business process both familiar and highly important to most organisations: selecting and on-boarding job candidates.
The basic components would start with a training data set: a complete history of all candidates selected and hired, their key attributes, how they were on-boarded, and their eventual performance in the organisation. Next, an analysis engine would extract key features that contributed to candidates’ success and create a recommendation engine that would rate new applicants and their likelihood to thrive at the organisation.
So far, this scenario is somewhat similar to data analytics, except that the algorithms decide which factors matter and which ones do not. Machine learning goes one step further. It processes ongoing results of those candidates, and continually updates its recommendation engine rules over time.
It learns from actual experience, and thus it makes better decisions over time. Think of adaptive intelligence as data-driven learning at vastly increased speeds compared with humans.
When applied in a database, autonomous technology can not only automate the process of cleansing and organising data, it can also ensure patches are applied and the data is secured. And when applied in a data warehouse, autonomous technology can interrogate data to find correlations and patterns across structured and unstructured data, and then present these as insights back to business users.
This is not a vision of the future, it is a capability that Oracle is making available to the market now. And it can do all of this with minimal human intervention.
Remove complexity, add value
The key difference with autonomous technology is that it eliminates complexity.
This frees people from performing many of the tedious tasks associated with managing backend technology, allowing them to focus on tasks that will make a real difference to their organisation and their customers.
As technologies such as AI, machine learning and intelligent process automation become more widely available, finance leaders want to know: How can these technologies help me in my business?
At Oracle, we are embedding intelligent digital assistants into our products and applications. In finance departments, digital assistants can perform similar functions to automate repetitive processes that consume employee hours – time that could be better spent on higher-level tasks such as faster decision-making and architecting a new financial strategy. Soon you’re going to see digital assistants help your organisation speed up financial year end, manage budgets, and perform financial forecasting.
