It’s said that Covid-19 sparked 2 years of transformation in 2 months. While that figure is hard to quantify, there’s no doubt that the pandemic bumped the priority of transformation initiatives up on the c-suite’s agenda.
For the mass majority of companies, keeping up with the pace of transformation is a struggle and with roughly 60-80% of transformation projects failing, many need all the help they can get. That’s why we caught up with Prakash Senghani, Co-Founder of Saifety.ai (a start-up concentrating on construction technology and the use of Artificial Intelligence to improve safety and productivity) and Head of Digital Delivery at JLL.
Prakash is an expert in innovation, change management and digital construction who holds expectational knowledge in rolling out internal processes and developing innovative solutions that bring efficiencies along the digital journeys.
Here’s what Prakash had to say.
Digital transformation for me is a change management process, more specifically its success lies in changing the mindsets of people. Any digital tool, regardless of how innovative it is, is useless unless people use it. As well as impacting people, the outcomes of digital transformations should focus on bringing efficiencies to business practices as well as nurturing new business lines.
With technology, companies should constantly be transforming; I know this may sound cliched, but things change and develop at such a pace that standing still means that you fall behind. Some organisations wait until their competition starts a transformation programme, others when regulations force them to, both indicators tell you that you are too late.
Transformations should be embarked upon as part of strategic initiatives to improve areas of an organisation such as delivering safer working conditions, reducing risk, or increasing margins for example.
I think that the promise of artificial intelligence (AI) will have a huge impact on the way tasks are performed across many industries. AI is not without its challenges, but it has the potential to super charge other innovations and solve many human challenges both great and small. In the near term, other technologies I see making a difference is the continued proliferation of the Internet of Things (IoT) and 5G. As bandwidth and reliability increase we will see more and more devices connected and collecting data, adding to our understanding of the world and helping to make it better in many ways.
Attitudes towards change and acceptance of continually improving it are key to having a digital-ready culture. It is essential that the most senior leadership not only buy into the digital initiatives, but also live them.
Being irrationally attached to existing systems and processes along with fear of change and cost are the main barriers. That’s not to say any of these should be ignored, they are barriers for a reason and should be understood and overcome, not pushed aside or steamrolled.
Attention around AI ethics is getting fully warranted and needed. We have to have the debate around the role and therefore the responsibility AI has in society as it becomes increasingly pervasive. Its use in self-driving cars is a commonly cited one; who is liable for the accident the car has after a decision made by the AI powered computers controlling it? Is it the owner of the car, the manufacturer of the car, the coder of the algorithm or a combination of them?
The other side of it is the ethics of training AI models with intrinsically biased information. There are well documented cases of AI enabled applications becoming racist, sexist and homophobic because of the data they’ve been trained from or the imbalance of the available data.
I don’t have the answers, but collectively and openly discussing these things is the only way to find a workable if not perfect solution.
I think it is difficult to generalise as the applications and uses of AI are so varied. But in most cases, I think that the training data has the biggest impact on the outcomes and so should bear most of the responsibility.
Yes, if you are in doubt about whether what you’re doing impinges privacy then don’t do it. The promise of the use of AI can easily be lost if privacy concerns become widespread, the same way the promise of social media has been. There are some great lessons to be learnt from social media’s soul searching, the biggest is that there will be unintended consequences to the mass deployment and uptake of a technology. We must put in checks and balances upfront to ensure that any developments are constantly being referenced to original goals before being pushed out.
I read... A lot. I easily spend 4-5 hours a day reading, not necessarily directly about digital, but with digital being so ubiquitous across industries and geographies some link to digital is never far away. I’ve recently become a fan of podcasts which I listen to whilst commuting or exercising, it’s a great way to digest information and opinions efficiently.
Communication! Communicate why you’re doing it, when you’re doing it, how you’re doing it, who it will impact, and most importantly, how it’s going at regular intervals. Having a robust feedback mechanism is also important but again it comes back to communication.
I guess you don’t until you actually do it. I believe that everybody is innovative, as humans we are hard-wired to solve problems and it's the reason we’ve succeeded (perhaps too well) as a species. The tough part comes in marrying this innate innovative spirit with business acumen. Like with much of what happens in the technology world there’s a bit of trial and error to get teams working towards innovations that truly deliver value changes.
Strong leadership, clear vision, acceptance of failure and flawless communication. Ideally all in equal measure.
I personally measure it in how many people are talking to others about an initiative, if you can get to a stage where you’ve advocates are telling others how good or useful a transformation element is - you’ve won. The business always likes to have hard measures though such are returns on investment. Here I try to clearly define the different types of ROI, the hard numbers affecting top and bottom lines and the soft intangibles such as market, customer and employee perceptions.
My favourite one so far has got to be the development of a safety management platform which uses a chatbot as its interface. The idea on the face of it is simple, take a means of communication which has become by far the most popular way to do so and integrate a workflow that can directly save lives.
Being willing to do/use the products or techniques that you espouse. There is nothing better to aid adoption than seeing leaders and trusted people doing things that they are asking you to do. The ancillary benefit of doing this is that you get to see whether what you’re asking others to do actually works or how you can make it better.
Start small by automating manual tasks. Don’t try to digitise at the same time as introducing a new process if you can help it. Start by understanding the existing way of working, digitise that, get acceptance then improve it by adopting efficiencies.
Chatbots are going to continue to develop and become more widespread, in doing so they will become better at humanising computer interfaces. AI which automates admin intensive tasks, such as data analysis and document review is another area of growth I feel.
Fear created by a lack of understanding. I mean this from the lack of understanding of what the AI does as well as what it doesn’t.
I think they get more of a voice at the top table, although the immediate conversations will be around using digital for business continuity, these new found voices will be able to influence broader digital objectives.
Be inquisitive and take all opportunities that are given to you, you never know where they’ll take you.
Have a question for Prakash? Drop him a message on LinkedIn!