Enterprise IT – learning from a new teacher

Enterprise IT – learning from a new teacher

Mark Twain had a way of capturing everyday difficulties with a trademark sense of humor. He knew that everyone likes crystal-balling, but, as he put it: “Prediction is very difficult, especially if it’s about the future”. If you think I’m getting my defense in early with that, you’re absolutely right. However, there are some strong pointers to suggest that enterprises are moving in new directions, many underpinned by lessons learned from, or imposed by, our experiences as consumers.

1. Reinventing the Enterprise workplace

If you thought that the rate of change in business was spectacularly fast already, hold on to your hat – the next wave of change will disrupt much of the IT we took for granted within the enterprise workplace. When it comes to the immediate specifics, in 2018, we predict that large enterprises will take on at least one of these four essential building blocks to reshape their workplace.

I. The end of the (dividing) line

For a long time most enterprises fought hard to stop employees using their own technology at work. IT departments built a ring fence around enterprise systems, and allowed employees in through a single point of access – usually a laptop. If that’s still what it looks like where you work, get ready for change. Forward thinking enterprises have embraced the idea that employees work better, faster and with more commitment, using technology and apps that suit them – rather than the IT department. The upshot will be a blurring of the dividing line between the enterprise employee and the consumer, or removing it altogether. Let’s drill into that a bit deeper. A few years ago corporates were banning Facebook, fearing it was deflecting too many employees’ attention from actually getting on with their work. Now they’re encouraging its use, as perhaps the most effective and authentic way to convey an organization’s values, messages and marketing. Sure there are risks attached here, but if you hear something (positive) about a company during the course of a normal, social interaction, you are far more likely to give it credence than from any paid-for ad. There’s a big “but” coming, and it’s compliance. I don’t have any hard and fast answer here, and there is no standard solution, but I encourage organizations to try and find the balance between remaining compliant and providing your employees with this freedom and flexibility.

II. What’s the most valuable thing that you do?

Economists describe the underlying cause of the enormous wealth created by Google, Facebook and Amazon, as their ability to harvest “externalities” – things that happen during interactions that are not reflected in a market price. In the case of Facebook, for example, you don’t actually pay for access, but you do leave behind an enormous data footprint that can be (and is) mined for behavioral insights. It’s those glimpses that enable Facebook to make money through advertising. The power of data as an externality is well understood now, and most enterprises are already evaluating what data is generated in the course of our normal business operations. What does it tell us about our customers or the market? What additional data could we collect if we changed the way we work? And many companies will continue to collect data even without a defined use for it. Let’s call this approach ‘collect data now and decide what to do with it later’: this will increasingly be the norm.There are challenges on this path. How exactly do you capture, store and retrieve every piece of data? How do you uncover the value that resides in it and then tie the whole map together to make sense of it? And, of course, how do you do all this in a way that respects the privacy and legal rights of the people or entity leaving the data trail? The arrival of EU GDPR in May this year, to name just one piece of legislation, is a reminder of the challenge here.

III. It is what you wear (not the way that you wear it)

Wearable technology in the workplace is about to go mainstream. The first demonstration scale applications have already happened – for example, Fujitsu has been working with DHL to improve the safety of its drivers and other road users. But think about the wider potential here: people are usually found at or near the point of interaction with the customer. What is taking place around your employees – factors like heat, humidity, noise, traffic and stress – could potentially provide invaluable information about what your customer is experiencing. And the aggregated data – externalities again – could be the signal you have been waiting for to respond better, or even completely change the way you interact with customers. You need to work out the implications of wearables for your business and how to get the most out of them.

IV. Right-skilling

Offshoring was a favorite corporate maneuver of the 90s and naughties – moving work across the globe to where it could be performed in the most cost-effective way. Even at the time, many predicted that this approach had a limited shelf-life, as costs rose in offshore locations, driven by skills shortages, and as customers became disenchanted with service levels. So where does that leave us? Technology has moved on in the intervening years to a point where it potentially solves the desire to locate service near to the user, at a price the customer is willing to pay. This is not about the wholesale automation of work, or removing people from the equation, but the use of technology to fill skills gaps, and to provide service locally by people with skills that already exist in the labor pool. Consequently, we are in the early stages of a shift away from geography as a source of competitive advantage towards automation. In particular, Artificial Intelligence (AI) holds the potential to fill the skills gap, and enable local labor pools to find work that matches their skills and aspirations.

2. For my next witness, I call AI to the stand

While we’re talking about AI, you can be confident that the legal industry is taking a good look at the potential implications of this technology. Some say we have already had the first AI legal case, when data from an Amazon Echo device was subpoenaed in a California murder investigation. I think that looks like a case where the police hoped Alexa happened to be recording during a crime, more than anything to do with AI. Nevertheless, it is only a matter of time before the grey area of responsibility between, for example, the actions of a driver or a doctor and those of the AI system aiding a person are challenged in a personal injury claim, a medical malpractice suite, or a data privacy infringement case.

3. Enterprise AI – not there yet

Let’s stay with AI. 2017 was the year when everyone decided they had an opinion about AI. Not all of them were right about this. So far, what we have seen at the enterprise level has been tactical improvements. I am still skeptical whether many pilot projects will deliver on expectations. However, once this phase is over – and I think that will happen quickly – I predict a more systematic, scientific approach to the use of automation and AI, and one that will lead to significant breakthroughs.

One common theme of these predictions is that underwriting most of them is the consumerization of IT, in which enterprises are learning from consumer behavior and leveraging this insight to support future strategies. The compartmentalization between us as employees and consumers was always bizarre, driven purely by the limitations of technology, and appears to be ending. There is little chance that the younger workforce is ever going back to the old model, and forward-thinking enterprises have already grabbed this as an opportunity to find better ways to work and to deliver better service to their customers. I predict that 2018 is the year you should join them.

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