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 prioritise data-driven decisions benefit from 4% higher productivity and reported 6% higher profits. These companies treat data as an asset.
Upskilling the workforce
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 up-skilling 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 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 increases, 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.
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 upskill 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 to enable them to make data-driven decisions. Enterprises collectively experience billions of dollars in revenue loss each year due to project failure, missed timelines, and cost overruns. Our software will safeguard the enterprise against risk so teams are empowered to focus more on what’s important – value creation and more satisfied customers. As 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 learn from past project data. Project Managers don’t require the expertise of an experienced data scientist or 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 “technology democratisation”.
This level of transparency and access to data, analytics, and insights all help project managers to be more effective decision-makers, hone their people skills, and ultimately drive better business outcomes. Soon businesses can move from descriptive analytics, “What happened?”, to predictive and prescriptive analytics, “What’s next?”, and “What should we do next?”.
Data-driven decisions – The future
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 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 a competitive edge. It’s time to ask: Is your enterprise ready?
Read our guide to learn how to make ‘Faster, better, smarter decisions’.