June 22, 2022

One giant leap for enterprise: data science

— Author: Amanda Freick

A data-driven approach has caused industries to advance rapidly and innovate in arenas vastly beyond their silos. That’s the new normal that traditional leaders find hard to keep up with. Data science is the next big leap for enterprises. They recognise that they need it, but struggle with how to implement it successfully.

Data doesn't lie

I have worked in the energy utility industry for over a decade as a third-generation engineer. I am on a personal mission to enable a responsible energy future while being realistic about the changes it needs. I am, however, optimistic about what data can do. When the IT/OT boom came into the energy industry, there was a learning period because it came from a non-utility industry. Companies today tend to feel the same way about data science. They don’t understand it. But you’re dealing with data from your own company. Data doesn’t lie! It points you in the right direction.

As an evangelist for open innovation over the last five years, I discovered that allowing your company to innovate on top of data helps you leapfrog your competition. If you bring the right brains in and allow their algorithms to talk your data, it doesn’t matter if you’re selling purses or electrons. There are things you can optimise through data science that will accelerate your enterprise. It’s the golden ticket to growth.

Finding your open strategy

In the era of digital disruption, any strategy for growth must be an open strategy. Organisations that engage with Altruistic and our expert crowd of data scientists, find themselves harnessing the creative capabilities of 3000+ brilliant data scientists, hungry for the challenge. Embracing open innovation is fantastic because you can only fail forward. The costs are lesser. The risk is lesser, and the time you spend is lesser. You haven’t spent a tonne of resources building up your R&D. Where you once bet your R&D budget now a handful of ideas; you now have hundreds to choose from. If one doesn’t work out, you can move on to the next thing.

Innovation comes hand in glove with a diversity of thought. For enterprises looking to transform, a diversity of thought means bringing fresh ideas at a scale that traditional recruitment or contracting scenarios can’t do. Brilliant minds who have never been around your problems before will give you ideas you’ve never seen before.

The network effect of a convergence of thought

When organisations use the power of a crowd like the one we have in Altruistic, they’re enabling value creation from external human capital. It’s powerful because your most important asset – the data scientists – aren’t doing it for money. That’s a perk for them. They could get jobs at CERN and NASA and the big tech companies and make half a million dollars a year. Many of them do. Yet, they’re participating in the challenges because they love the challenge of it all. Their brains are wired to solve problems, and they want to make a difference with really cool projects.

Open talent brings in solutions from a variety of industries to enterprise problems. Once they switch their former experience on its head and then apply that to your challenge, you’re getting an exponential increase in results. Your growth is faster, and it’s far more cost-effective than a traditional echo chamber of thought which goes at a snail’s pace.

Together we innovate, esponentially

Enterprises often pretend that digital transformation strategies are a silver bullet. Everybody tends to begin by implementing huge digital strategies or innovating for innovating’s sake. Reports show that 85% of artificial intelligence implementations fail to deliver. That’s billions of dollars wasted each year. Open innovation lets you deploy technology in a holistic and useful way for the needs of your specific business and not because that’s what the markets are telling you to do.

Getting started with data-science-based open innovation requires understanding that you’re sitting on more potential than you realise. A simple data audit reveals where resources need to go. You need to commit to taking the next step in your organisation through the lens of data. And, solve a real problem with measurable results to your business.

Let's think about a Fortune 500 fashion retailer Altruistic worked with. Using their available data and one algorithm, our crowd of data scientists decreased their stockouts by 41%. Every one of the items on the shelf had an increase in average sales of USD49. 41% of stock out is a big number. That’s millions of dollars for this company.

With their available data, enterprises need to examine how they optimise it. Traditionally, business functions look at data and formulas to optimise them financially. They tend to be metric-driven. Data scientists are not just optimising for metrics but finding new insights that can give businesses true competitive advantages over their competitors.

Companies need to think about how they’re future-proofing themselves. AI helps get the predictions right. It’s not sure-fire right now, but seeing failure and trends before they hit helps. Have your eyes wide open, and remain honest and transparent about the outcomes you want. Then, deploy the technology that’s right for you.

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