COVID-19 has undoubtedly sent our work lives spiralling into the unfamiliar. From conversations in the canteen with our colleagues, to virtual video calls five times a day, it’s safe to say that work is no longer defined by turning up to a physical office-based desk for seven hours a day. As our working habits continue to shift, more and more organisations that might have before been slowly considering transitioning its operations over to the digital era, have now been forced to do so. Interestingly enough, the reaction has generally been quite positive. It has spurred a new way of thinking about technology where it’s no longer a ‘nice to have’ option that might help to enhance business productivity, but rather, digital technology is the future, and quite simply put, the changes we’re seeing today will make or break businesses that don’t take the time to see its value.
This digital revolution is not just taking place in our working lives. We’ve been forced to shop online. Learn online. Meet friends online. Join Netflix parties online. Take exams online. The list goes on. This mass adoption of the digital world is now being considered, by many, the answer to the UK’s ongoing productivity puzzle. For example, according to a recent Gartner survey, 41% of employees are now anticipate working remotely in a post-Covid world. What we’re seeing is that many of us are planning for a future that before didn’t seem plausible. The question, therefore, is what technologies do businesses need to start adopting now if they are to help shrink the current productivity gap?
A well-connected infrastructure
The digital businesses of the future will require a well-connected infrastructure. Data is moving into a completely new paradigm whereby digital transformation can really start to take off. This means that the way businesses operate, transform, and engage will be totally different, as it will be much more data-led. Therefore, fail to get your data and application integration strategy right, and any efforts to digitise your services and offerings will not get off the ground.
Building a solid data strategy for your organisation
The challenge is many organisations still rely on a small number of data scientists or business analysts to manage, make sense of, and analyse all of its incoming data – and there simply aren’t enough of these individuals to go around. Relying on a small set of people is a roadblock which stifles innovation and reduces the timeliness of insight-led business decisions. An alternative which can remove these blockers is to centralise data and provide searchable data catalogues, which can democratise the data and make it accessible to all authorised employees. Artificial intelligence plays a key role in enabling this to happen, automating the integration and centralisation of data whilst also building a self-maintaining, searchable catalogue of an organisations data assets.
Embracing AI and automation
Productivity relies on three key things when managing complex data environments. Firstly, it’s important to enable self-service analytics for the less technical users. Secondly, machine learning should be integrated into any platform to automate data integrations and data discovery. Finally, data lakes ought to be deployed to manage and support in the automation of digital transformation solutions.
For all these examples, it is possible to apply AI to data management to speed up processes, increase the quality and availability of data and to further streamline it. Our AI platform – CLAIRE – is a great example of putting this into practice. With integration tools that connect to the cloud, it is possible to automate data management with AI and machine learning to ensure any anomalies are detected and that the data is managed, at speed. What’s more, it’s about ensuring that you have a process in place to simplify data cleansing, stack a high-quality data pipeline and deliver the insights needed from the data warehouse. Getting this right can save a lot of manual labour, and reduce the need to worry about human error, particularly as remote working is likely to become the norm.
The pros and cons of AI and ML in DevOps
Ultimately, productivity in the ‘new normal’ is going to rely much more on digital technologies than we can even begin to imagine. In fact, businesses digital transformation journeys have been sped up, as a result of the strain that Covid-19 has put on them. So, whilst many businesses do not yet have AI-led data management platforms and support tools in place, it wouldn’t be a bad idea to consider one in order to start seeing an acceleration of digital transformation initiatives and an accelerated return in the value of your data.
