As the world continues to embrace a digital first mindset, Seth Finegan looks back on key developments over the last decade and argues that the most powerful digital transformation is still to come.
What does great digital transformation look like?
Part of the accepted answer is the wholesale re-organisation of people, technology, data and processes to create new ways of working that trigger step-changes in productivity and innovation. Great transformation goes beyond delivering better user experiences; it delivers fundamental changes in what we are able to do as well as how we are able to do it.
But digital transformation isn’t just about technology – it’s about people and that’s why change has to be based on sound ethics. If the purpose of transformation is to do good in our lives and society, then being great will require more than changing business models and ways of working.
At our recent Digital Leaders Week Salon in Manchester we discussed latest digital transformation trends and debated what makes transformation great.
A common theme was the importance of achieving ethical, inclusive transformation that put people at the heart of its purpose and the way in which it is achieved. This might best be described as transformation for the people, by the people. Or to quote my colleague Elizabeth Vega in her interview with Kate Russell at the DL Conference, transformation that is “equalizing” not polarizing.
"Increasingly our human intelligence is working hand-in-glove with Artificial Intelligence"
To aid our discussions, we looked at the three most important waves of digital transformation over the last decade.
The first focussed on front-end design, transforming the UX and front-end services – better websites, user centred design and agile development methodologies. This is mostly focussed on relatively simple, single distinct services that made it easier to do existing tasks, like renewing your car tax, as a consumer rather than transforming the supply of the service.
Wave two has focussed on back-office automation, targeting deeper organisational transformation of not only the front-end services but the back office as well. This work re-organises workflows to create more automated organisations whose workflows are driven by their customers not their staff. This wave realises time and cost savings on both the consumer and supply side so, taking an example from the Ministry of Justice for instance, innocent victims of crime can now apply for and be awarded compensation more easily and quickly whilst the agency that delivers the service has reduced its operational budget by a third.
Wave three is taking advantage of advances in data analytics and Artificial Intelligence fuelled by the ever increasing volumes of data sourced from wearable tech and the IoT. In these environments, automation has taken a significant step forward, connecting to sensors that feed high volumes of structured and unstructured data into digital organisations.
"One answer lies in ensuring the next wave of digital transformation is delivered by ever more diverse teams supported by in an ever more diverse supply base."
Increasingly our human intelligence is working hand-in-glove with Artificial Intelligence to cope with such volumes, curating the learning models and making step changes in decision making effectiveness not just operational efficiency. For a fantastic example of where AI is beginning to have an impact look at the work the NHSI are doing, using Machine Learning to unlock insights in patient safety records here.
There is so much promise in the type of work that the NHSI team, led by Lucie Mussett, are doing with AI at NHSI. But how do we make sure the new opportunities that AI unlocks triggers great, ethical transformation? And what do we, as leaders and innovators, need to do to ensure this next wave delivers positive outcomes that are inclusive and sustainable?
One answer lies in ensuring the next wave of digital transformation is delivered by ever more diverse teams supported by in an ever more diverse supply base.
If AI models are trained and curated by an elitist few then we can expect implicit (and explicit) bias to be part of our outcomes. We have already seen problems with bias in facial recognition systems (read here for example) – and, as AI assumes a bigger role, problems with bias could become more pronounced and harmful unless corrective measures are taken.
If we put the interests of the user, our workforce and society as a whole at the heart of the design and application of AI then the next wave of digital disruption could not only achieve greater outcomes but be a genuine force for good.