Leveraging big data with AI to rejuvenate legacy systems

Jul 19, 2019 · 3 min read

Legacy systems get a bad press. They are blamed for holding companies back and costing them unnecessary money. One CEO even claimed that “God created the world in seven days because he didn’t have to port anything from legacy systems”.

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But legacy software is like the humble work van — although it doesn’t look as sleek and shiny as a sports car, it’s getting the job done every day. And just as you wouldn’t want a sports car to deliver a load of concrete, ditching legacy systems completely could be a bit like throwing out the baby with the bathwater.

Fortunately there is a middle way — incorporating new technology such as AI and machine learning to work alongside and rejuvenate your aging systems.

Legacy systems of course provide continual problems. They require significant maintenance, which becomes increasingly costly the more outdated they become, especially if vendor support drops away. They are generally monolithic and often overly complex meaning that experimenting with new technology could cause unforeseen and complicated cascades of problems. It can even become difficult to find technicians who know how to fix it. All of which means 43% of CIOs believe complex legacy technology is a significant barrier to digital transformation, according to Logicalis Global CIO.

The problem is that most organisations have neither the time nor the money to completely overhaul their systems, particularly if they are still doing the job. If it ain’t broke, don’t fix it is a powerful mentality, especially when completely overhauling your stack could put you in a precarious financial situation and lead to a temporary loss of momentum.

The good news is that AI can be integrated into your stack in a relatively seamless manner. The main issues are data and staff. Machine learning needs access to all your data all the time — that’s how it learns. So data silos and ringfenced data won’t work. Freeing up data, ideally to the Cloud, is key as is having select staff who are fully up-to-date and proficient with machine learning frameworks.

The benefits to integrating Ai into your stack are great and will only get greater as enterprises generate ever increasing quantities of usable data. Think of the vast amounts of content just wallowing idly in your organisation’s “data landfill”. AI can drill into that, sifting the useful from the not-so-useful, identifying those little nuggets of information to recycle and those to throw away.

With stricter compliance rules around what data can and can’t be stored, it is becoming increasingly vital that this kind of data sorting is done, or hefty fines could follow. Once your data landfill has been cleansed and streamlined, you can begin to use it in an integrated way to benefit the organisation as a whole moving forward.

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The enormous quantities of data swashing around within global distribution systems and logistics management systems added together with the complementary applications and software that have been added to the tech ecosystem of the business over the years — means there’s a lot to work with. Sciant’s combination of skills and experience in system integrations and data visualisation together with machine learning/AI can optimise the performance of your tech stack, giving that legacy system a new lease on life.

Time to stop thinking of legacy systems as the enemy and more like trusted old friends who need a little push to keep them ticking along. Integrating AI into your systems can do that without the headache of cataclysmic overhauls. Think back to that humble work van now equipped with an intelligent self-driving system and you’re thinking along the right lines.

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