In a recent episode of the Go beyond disruption podcast, we interviewed data and decision scientist Elaine McVey to learn more about data and decision science, how data impacts business decision making and how to drive value from your data. She also provided insights into how finance and business leaders can partner with data scientists.
CIMA Insights: What are some examples of business problems data science can solve?
Elaine McVey: In addition to having data science elements that are part of a product, data science can also help companies optimize how they're carrying out their business. That can mean a deep understanding of how customers move through the sales pipeline. It could be measuring how customers use products, which provides a much clearer picture of what's valuable and what's problematic with those products. It can also help quantify and predict the impact of the work a company is doing so it can be communicated to customers or investors effectively.
CIMA Insights: What's the difference between data science and decision science? Or is there one?
Elaine McVey: In my view, there's overlap between data science and decision science, but they're not the same. Data science can cover a whole range of uses of data and algorithms, some of which could be aimed at informing decisions and some of which might be part of technology. Decision science focuses on human decision making, and that includes the use of data to make decisions but also extends to other kinds of information that could impact decisions. For example, it takes into account the ways that humans tend to make decisions in predictably biased ways.
CIMA Insights: Tell us a little bit about what your day is like as a data/decision scientist. What do you do day to day?
Elaine McVey: My job is to make sure that everyone within the company has the data and information necessary to make effective business decisions. This includes integrating data across departments to help department leaders make well-informed decisions about how the parts of the business are working together. I also focus on the ways we make decisions and cultivate a culture of effective decision making within the company, considering decision making frameworks and thinking about some of those human cognitive biases.
CIMA Insights: PwC’s 22nd Annual Global CEO Survey revealed that organizations are still struggling to use data to get actionable insights, and that one of the main reasons for this is a lack of analytical talent. Is this due to shortage of data scientists or a lack of shared understanding and knowledge across the business?
Elaine McVey: This is a perplexing problem as people make big investments in data and analytics capabilities, and yet they still have this substantial gap in what leaders need to know. Analytical talent is an important piece of this. The good news is that the resources for people to get data science skills training are better than ever. We can help address that talent gap in part by allowing professionals in other areas to add data skills and combine those with their subject area expertise.
CIMA Insights: How can finance and business leaders work best with you and your decision science team?
Elaine McVey: It’s about being open and people on both sides not being afraid to admit what they don't know. People on the data side shouldn’t be intimidated by their lack of understanding of finance, and people on the finance side shouldn’t worry about not understanding all the technical parts of what a data science team does. Just start talking. Start conversations with statements such as “This is what I think I need,” “These are the problems I have” and “These are the questions I can't answer today.” You can then talk about how to work together to address concerns.
CIMA Insights: You brought attention to the fact that sometimes we have to be comfortable with not knowing. I think that's so true. We are in such a period of rapid change in business that we can't know everything all the time.
Elaine McVey: That's right. I think those conversations become effective when people are comfortable with that and comfortable with lots of functions needing to come together to solve problems.
CIMA Insights: What advice would you give accounting and finance professionals about partnering with the data science team?
Elaine McVey: It’s important to bring the problem you're trying to solve and a willingness to ask for help to get what you need from your data. There is a real opportunity for these two functions to learn from each other.
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