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The future of data science: Evo’s predictions of six developments in data science in the 2020s

The way we see it at Evo, data science is the future, but what does the future of data science hold? We asked some of our data scientists to share their thoughts on how the discipline is going to evolve over the next five years, as well as what data scientists will need to know to stay at the top of their field.

Here are six developments in data science that Evo data science experts Roberto Sannazzaro, Tobia Tudino, and Giuseppe Craparotta predict will happen during the 2020s.

1. Our capacity to make accurate predictions will improve.

Everyone in the industry understands that the more data we have, the better we can predict what will happen. If data scientists can continue to advance technology using artificial intelligence to keep up with this influx of data, predictions will get better every day.

For data scientists, this presents both a blessing and a curse. As Tobia noted, “As we continue to create new technology, the challenge is to balance innovation with support systems to handle the data… There is this urgency to develop stuff using every resource available, but if you don’t develop it in the right way, it can crash and you’ll need to start again and again”. In the next few years, the challenge will be knowing how to leverage data in the right way to ensure optimal progress.

Evo is determined to carefully balance these demands and increase the accuracy of our own predictions in the 2020s. Giuseppe shared one important way Evo is already setting itself up to make this prediction come true: “Evo’s capacity to use data has improved a lot as we’ve worked on data standardization. This means all parts of the model can benefit from new features so that we are more efficient”. 

2. Data scientists will need to focus on developing new skills every day and be flexible in how they approach their work.

Successful data scientists need excellent technical skills, but these change regularly as the industry advances. That’s why Roberto said, “To succeed as a data scientist today, you shouldn’t be afraid of anything new. You have to always be ready to learn something new from scratch every day… 90% of our job is learning and applying something new”.

Giuseppe agreed, stating, “The most important skills for data scientists are to be smart, to adapt quickly, and to feel passion for what you are doing”. Data scientists who refuse to innovate will only fall behind those willing to take on the challenge of attempting a better way. 

3. More companies will embrace using prescriptive analytics and data science.

We’ve reached the peak moment for companies to adopt data science with the goal of making better decisions informed by prescriptive analytics. More and more businesses are realizing the potential of such a decision. Giuseppe said, “I see that there is an enthusiastic adoption of data science in companies; I think managers are convinced that they should grab the opportunity. This belief has been growing over the last few years, and I think we’ve reached a good level of awareness of its potential”.

Tobia continued, “There are so many problems that data science can solve… As more people discover these capabilities, more people will adopt the technology to their advantage”. In 2020 and onward, more companies will embrace the kinds of solutions only possible through the application of prescriptive analytics and data science in general. 

4. Data scientists’ ability to explain how their models work will become increasingly important.

Despite increasing excitement about the opportunities presented by data science, what still holds most companies and individuals back from using it to improve their results is a confusion about what exactly data science is.

Roberto explained, “I’ve seen that many data scientists have a difficult time explaining how the algorithms used actually work… This causes a fear that leads companies to choose easier to understand but often less innovative models”. Tobia continued, “Data scientists need to have coding expertise for sure… but you also need to be able to present and explain. It doesn’t matter how good you are at coding if you can’t explain what you did”. Unless data scientists can express the science clearly to less technical individuals, they risk significantly holding the field of data science back in the 2020s.

Data scientists have a responsibility to help people understand how the technology works, so they, too, can benefit from its full possibilities. Luckily, this is possible— and something that data scientists here at Evo are prioritizing. Giuseppe emphasized, “What I see is that clarifying how the engine works and what causes a recommendation of a particular action is important”. When our partners understand why we suggest something, they are more likely to implement it— and therefore more likely to have larger success with data science. 

5. Data science will reduce inefficiencies in the private and public sector to make our lives better.

According to the data scientists at Evo, data science has the potential to change the way we live our lives for the better. This will affect everyone. As Tobia put it, “Data science will be a great tool to improve society’s issues, everything from making public administration more efficient to predicting and preventing harms from weather disasters and earthquakes”.

These benefits will trickle down especially to those sometimes left behind by digital advancements. Roberto explained, “We can ensure that people on the margins of society, such as the elderly, disabled, or unemployed get the services they need when they need them”.

It’s not just the underserved who benefit from algorithms designed to identify who may need something before they realize it themselves, however. Delivering the right products and services to the right people at the exact time they need them is a major goal of data scientists across the world today. In fact, this is essentially what Evo’s supply chain algorithms accomplish in the private sector.

Evo aims to reduce inefficiencies that affect everyone by partnering with retailers. According to Giuseppe, today “we have more data about customers all over the world, so we are able to detect trends and patterns across multiple industries and geographies that we couldn’t a few years ago”. This additional predictive intelligence means that consumers in every unique market are able to get the exact product they need when they need it. Consumers are happier and better served, while companies sell more and develop better relationships with their customers. It’s a win-win. This capacity is going to continue to expand throughout the 2020s.

6. Data science will expand in ways we can’t yet begin to imagine.

Ultimately, the sky’s the limit when it comes to data science. We have no idea how much the field will advance over the next decade. The 2020s will be a time when its use grows and changes in exciting and unexpected ways. The pace of changes has reached such a height that it’s difficult to even just keep up, much less predict where we’ll be by 2030— or even 2021.

Tobia went further, saying, “There’s really a push from the data science world to change society in general. For example, there’s a lot of articles that show the academic world is not working [with the way we do business] anymore. There’s a lot of people pushing for things like nano-degrees where you can get a degree in six months and the professor can teach you the latest information very quickly. By the time you finish a degree in three to five years, it’s already too late. You’re behind the field”.

While we may not be able to predict exactly what the future of data science holds, Evo’s data scientists do all agree that data science will in some way form the “new normal” and so pervasive in its many forms that it will become a normal part of everyday life. As Roberto put it, “Data science will evolve into something that is embedded in almost every industry. At the end of the 90s, companies were emphasizing how much they used computers as a way to show they were keeping up, but nowadays no one mentions computer use because it’s just expected. It’s normal. Data science is going to follow the same path”.

Ultimately, the Evo family is excited that the future of data science is intertwined with the future of everything else in business. Giuseppe emphasized, “Unlike what was supposed by some analysts, I am convinced that data science will not die. It is not a temporary trend or technology. It will envelop the world in which we live today”.

Data science has a bright future as we enter a new decade. The future here at Evo looks particularly bright in the 20s, as well. As Giuseppe said, “If I look back at 2013, the word ‘prescriptive analytics’ had just entered the hype cycle for emerging technologies with the expectation that the concept would mature in the next five to ten years. Thus, we are now at a key moment, when we can demonstrate that these technologies are worth applying! … Evo’s algorithms have also hit a point of maturity, where we can get increasingly better results for our clients. Over the next ten years, Evo will continue to contribute to humans making better decisions using technology, which is an exciting future”.

About the author

Kaitlin Goodrich is Evo’s main storyteller who helps communicate Evo’s message to the world.
Kaitlin received her BS in International Affairs and Modern Languages at Georgia Tech and then an LLM in International Trade Law from the University of Turin. She worked in Latin America doing education outreach for U.S. binational centers and has since worked as a content writer for international clients.
In her free time, she likes to travel or curl up with a good book.

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