The road to digitalization, and the transformation into a data-driven organization, can be a rocky one. There are many reasons for this. Good technology is essential—but you also need more. Almost ten years ago, colleagues in SAS were already talking about the need to address people and processes as well as technology. They talked about working on processes across the analytics lifecycle, and the different roles that might need to be involved at different stages.
However, over the last nine years or so it has become clear that one of the biggest challenges to becoming data-driven is the difficulty getting employees to engage with data and data science. Put simply, success in analytics requires staff to use data and analytical tools. Without that engagement, it doesn’t matter whether you have great technology or fantastic processes.
Designing for deeper data science engagement
There are many ways to increase engagement. For example, co-creation can help to ensure that products, including technology and analytics solutions, genuinely meet customer and user needs. One specific example of that is design thinking, also known as collaborative design. The concept behind this is that innovation will be more successful if more people are involved, both on the development team and from clients—and it does genuinely seem to work.
Now, what if you’ve already invested in your analytical tools and you now need to get everyone on board? Another option is to use games to promote stronger engagement.
Like co-creation and design thinking, gamification has also been around for a while. It has been used in healthcare and wellness to encourage healthier lifestyles, such as doing more exercise. However, it can also work as a way to increase engagement with data science.
SAS has collaborated with HEC to create an online analytics game called Cortex. Each game includes a case study, dataset, leaderboard, tutorials, SAS software and SAS instructor time. There are three possible game scenarios: fundraising, customer retention, and credit risk. The fundraising scenario is based in a non-profit, and participants are asked to identify how to raise the most money in the shortest time, and most efficiently. The credit risk scenario assumes that you are a loan officer in a bank, and have to develop a model to evaluate potential client’s creditworthiness. Finally the customer retention scenario is to maximize the benefits from a customer loyalty campaign at a telecoms company.
Data science skills enhancement and engagement proof points
The game can be run over different periods. The SAS Cortex Analytics Simulation 5-Day Challenge was, as the name suggests, ran over 5 days in 2020 and 2021. It was aimed at students, with the prize being a virtual internship with SAS. The winner from 2020 reported that the challenge helped him to improve his skills, but also gave him valuable insights into how data can affect real world decisions, and how to get results in a limited time.
Another participant valued the daily webinars over the course of the competition. He reported that these helped him to use SAS Enterprise Miner more efficiently, and learn different modelling techniques, as well as getting answers to any questions. He was also clear that this was a very good way to learn more about a particular piece of software and how it can be used for predictive analytics.
Building play into data science training and development
However, Cortex isn’t only for students—and it isn’t only available at specific times. It is also available for both academic and business use as a training tool. Businesses can use it as part of a training event, or a standalone game. Participants can work individually or in teams, and just for a brief time or over a longer period. The game can be customized for different skill levels, so that you can involve teams with different experience of analytics, and everyone will still get something out. It could also be used as part of a recruitment exercise, to test and build potential employees’ skills beforehand.
Both employees and employers report that Cortex is useful. One employee said that he was impressed at what was possible without coding, because this saved time and allowed him to focus on fine-tuning the model. The Head of Data Science in one company in Finland reports that Cortex has been an excellent way to encourage employees to use the data science platform, and that it fits well with the company’s data democracy initiative. Overall, therefore, Cortex provides a useful way to connect remote employees, and help them to develop their data science skills.
Could gaming be the right way for you to increase engagement with data science?
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