If we really want to make automation work for us, we need to think bigger

By Julian Williamson, - Future WorkplaceService Intelligence

For all the talk of how analytics, artificial intelligence and automation are set to shape the world of tomorrow, it’s generally accepted in the industry that the technology being used to implement these solutions is relatively well-established already.

The real ground-breaking work comes not from what we’re doing, but how we’re doing it. Looking at the data available, what our analytics tools can tell us about it, and, most importantly, which bits are most useful in automating solutions to deliver genuine benefits.

As the modern workplace changes, and the workforce with it, the challenge faced by those seeking to automate processes is one of approach: to think more broadly about where automation can really make a difference.

This means breaking down siloes and examining workflows to assess where automation can be replicated across different areas of a business.

At Fujitsu, this is something we’re pursuing wholeheartedly and seeking opportunities to automate processes entirely, from end to end.

It’s through this broad-ranging approach that the real benefits – speed, accuracy, lowered costs – will be reaped.

Automating beyond the hype

Despite the hype that surrounds it, the reality of a lot of the most important automation is that it isn’t always the most exciting.

When we speak with our customers about their main technical pain points – areas of unnecessary strife that are resultantly ripe for automation – the same things come up time and again.

Take patching, for example. It’s an important process that’s existed for as long as I can remember, but it’s still a largely manual effort.

It’s processes such as this, which typically involve some automation (in this example, the tools used to download and trigger patches) but ultimately require a manual go-ahead signal, that should be focused on with a rethink.

One area in which we’re already achieving this at Fujitsu is device management.

We’re able to use analytics from remote monitoring of devices to spot anomalies and arrange for repairs or replacement before a device fails.

Not only that, but we can then automate that process of arranging repairs or a replacement – using a machine to locate and then dispatch the best human engineer to deal with the issue.

The next step on from this will be introducing cognitive AI that can understand the multiple contextual contributing factors to any one issue – allowing for an even faster, more accurate automated response.

Ultimately, the goal must always be end-to-end automation.

Sharing a broader view

As with any major shift in working practices, however, there’s an aspect of cultural change to contend with.

The case of end-to-end automation presents something of a Catch 22, in that the vision required to think big and spot opportunities often only comes once you’ve witnessed or come to understand the benefits.

In this same vein, the main results of successful automation speak for themselves: a process which is not only quicker and keeping costs down, but more accurate and, crucially, consistent too. It’s about freeing up human time and energy for the more complex problem solving that machines simply aren’t capable of.

Less obvious, however, is the positive effect on upskilling employees and developing their understanding of how automation can work for them.

Ultimately, we want to take people – that means both customers and employees – on the journey with us, because there’s little long-term value in leaving them behind or making them dependent on someone to do the automation for them.

Meeting the workforce needs

This will only become more important as the modern workforce develops.

Today’s globalized norm is for businesses to operate across territories and geographies, and for their employees to do the same.

Not only, then, do solutions need to work in a mobile context – something which our cloud-based and open-source analytics platform enables – but processes need to be consistent and seamless across work bases.

An engineer running a fix in Germany needs to feel confident that the same process will work when they attend a job in another region, country or continent.

Consistency is key, and must apply not solely to the output of the process being automated but to the implementation of the process itself too.

Making the most of it – automatically

We’re talking about the future here, but I don’t believe it’s a future that’s all that far away.

Analytics and automation are already helping to deliver a more efficient, seamless experience – but it’s largely occurring in small pockets and siloes.

In a workplace that’s increasingly agile, mobile, and digitized, these siloes are unsustainable.

Within the next year, we hope to have proven the benefits of scaling upwards and outwards and showing that the real value of automation is in end-to-end solutions.

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