How to get ready for ‘the next big thing’ in tech

Talk of the next big thing is rife in IT, but what action can you actually be taking to prepare for it?
11 February 2019 | 119 Shares

Portuguese President Marcelo Rebelo de Sousa waves after delivering the closing speech on the centre stage of the 2018 edition of the annual Web Summit. Source: AFP

There’s a time-honored saying in the IT industry. It’s that reply anyone can give when the discussion turns to innovation and the assembled group wants to know when the ‘next big thing’ will come around the corner.

“Oh, the next big thing? Well now, that’s about five years away,” said you, yes you.

Why five years? Well, firstly it’s quite a safe bet because software (or hardware for that matter) rarely experiences major platform shifts on anything like an 18-month (or even double that to three years) time period.

Apps come and go in that time, but the next iPad level change or the next Microsoft embracing Linux and open source type of change happens much more like once every five years— or in reality, more like once a decade.

So with that rough cadence for change in mind, what can your organization be doing now to think about the next big thing and how to work effectively with it.

AI will necessitate governance

One key trend on the next-five-year road ahead is automation. Not just automation in the form of functioning robots, but automation in the form of artificial intelligence (AI) enriched software controls that make a lot of business functions happen automatically based on defined and agreed business roles.

That automation is good news… and it will spread into so-called low-code application development where business users are able to use automated blocks of software to build apps just the way they want them.

All of that automation is good news… but there is an upshot, a caveat, and a major proviso. As we plug into more automated business, we will also need to ensure the right level of governance and compliance controls in place to ensure that the automated streams of the business don’t step out of line.

If your IT department (or indeed your CIO and CTO) haven’t been talking about (or at least mentioning future roadmap considerations for) that aspect of business technology life that we now call automation governance… well then, you may want to call a meeting. 

Smartness strategy

The list of ‘stuff you need to worry about that is currently emerging’ is long, but let’s at least add to automation governance controls with what we might, unofficially, call the need for a ‘smartness strategy’.

You could call it information and knowledge management, you could call it Business Intelligence (BI), or you now more informally call it the ability to determine your organization’s own smartness quotient at any given moment in time. A firm’s smartness quotient is defined as that amount of structured, parsed and categorized data that it has channeled into the right areas of database access to feed the right applications at the right time.

The smartness quotient is naturally multiplied by big data analytics functions that serve what become increasingly smart apps that (in and of themselves) also get smarter over time as AI and machine learning (ML) helps to tune their operation and make them even better suited to users’ needs.

Applying AI to your company’s operational business model and injecting its advantages into your applications and wider software stack without creating a core smartness strategy to monitor company knowhow, well… that’s not smart, is it?

Self-driving car status

Looking wider still, we can see many technologies that appear to exist somewhere in between emerging, still-nascent or at some more advanced prototyping and Proof of Concept (PoC) stage. These are developments that are pretty much on the road, but not altogether real yet… rather like self-driving cars.

What will be important going forward is for companies to understand how specialized each individual aspect of technology is going to get. There will be no Swiss Army Knife apps or indeed devices… a far greater degree of specificity will surface inside our IT stacks as it then manifests itself on our devices and inside of our applications.

This (above) core truth and the aforementioned splitting apart of our old monolithic data stacks will bring about a new need for what the industry likes to call decentralized data management. The future is all about knowing the intelligence is everywhere, so you need to do something about it, everywhere.

Once you’ve taken all the above on board and got yourself set up for all the change afoot in the medium term, you can start to make your long-term plans.

On what kind of timescale should the longer term focus? Say about five years.