At Galvia, we love to look into the future. And, well, what we see is a lot of C-level executives in boardrooms asking, “What does the data tell us?”
Over the last year and a half we have followed the numbers religiously as we steer a path out of the Covid-19 pandemic. Behavioural science is telling us that due to this collective experience, consulting the data will play a stronger role in C-level decision making in the future.
According to a recent Garter study, The Future of Decision, by 2023 data literacy (the ability to read, understand, create and communicate data as information) will become an explicit and necessary driver of business value and more than 33% of large organisations will have analysts practicing decision intelligence.
Such indications paint a rosy picture for the future. According to a study conducted by the MIT Centre for Digital Business, companies that are data-driven benefit from 4% higher productivity and reported 6% higher profits. These companies treat data as an asset.
Upskilling the Workforce
But like all things in life, good things come to those who prepare for it. Surveys are already indicating that the companies reaping these benefits are investing in digital transformation and upskilling their workforce.
But not all. In PWC’s annual CEO survey, 79% of CEOs said they did not feel ready to take on the business strategies in front of them with the skills and talent level of their current workforce.
Not surprising I suppose when the impact of the pandemic has delivered 10 years’ worth of anticipated change, in less than 10 months.
We know that digital transformation requires investment in AI, data analytics and automation but what exactly are the workforce skills needed to unlock the benefits of transformation and thrive in an era of disruption?
Does it mean that we all have to drop everything and retrain as data scientists? Not exactly. In fact, as technical integration deepens and the need for technical skills increase, so too does the need for skills that can’t be replicated by machines or algorithms, like active learning, leadership and social influence, creativity, ideation and originality.
But what’s really interesting is that the technology itself is actually enhancing the skills and agility of the workforce.
The Perfect Combination
Take PepsiCo for example and their quest to make the perfect Cheeto. Denis Lefebvre, SVP of their Global Foods R&D, explains how the company leveraged Microsoft‘s autonomous system. First the engineers trained the AI on all the parameters to make the perfect Cheeto, then they assessed how the AI is making decisions through millions of simulations: “The AI is continuously tracking the performance coming off the extractors and flags real time if there’s an issue so the team can intervene very fast. What’s great about it is that it actually upskills our workers. It’s actually the perfect combination of human and machine” concludes Lefebvre.
Transparency and Access
At Galvia we are developing a machine learning tool that will serve as a virtual co-pilot to project managers in large enterprises. Enterprises collectively experience billions of dollars in revenue loss each year due to project failure, missed timelines and cost overruns.
Our software will safeguard enterprise against risk so teams are empowered to focus more on what’s important – value creation and more satisfied customers. As a virtual co-pilot we will be on hand to alert, prompt and focus attention where and when it is needed.
Effectively our product has a suite of machine learning algorithms that learns from past projects data. Project Managers don’t require the expertise of an experienced data scientist of a software engineer to gain insights. Furthermore every project manager has access to automated insights via dashboards, reports and views in enterprise applications. This is what we term as “technology democratisation”.
This level of transparency and access to data, analytics and insights all help project managers to be more effective decision makers, hone in their people skills and ultimately drive better business outcomes. Soon business can move from descriptive analytics, “what happened?”, to predictive and prescriptive analytics,“what’s next?”, and “what should we do next?”.
Future of Decisions
It’s important to note that automation is not the end all and be all. It has its place. Automation is ideal where actions and work are repeatable but data can add intelligence. In general, machines and humans each have a role in effective decision making. Human decision makers certainly shouldn’t be replaced everywhere; rather, they should be complemented by the power of data, analytics and AI.
So let’s get back to that recent Gartner study on The Future of Decisions. The report flags that progressive organisations are already complementing the best of human decision-making capabilities with the power of data and analytics and artificial intelligence — to create opportunities to fundamentally change what they do. The quality of the decisions being made by these organisations is already giving them the competitive edge. It’s time to ask: Is your enterprise ready?