Often, executive leaders reach strategic decisions within a silo, based only on gut feelings and numbers lacking context. However, companies are beginning to recognize the need to not only capture internal and external data but also to better interpret the data to improve operational success and fuel growth. High-performance enterprises realize the value that data scientists can bring to the strategy table, and as a result, data and analytics are transitioning from a technical discussion to a business discussion.
In a 2016 PwC Global Data and Analytics Survey, more than 2,100 executives shared that their companies need to be faster and more sophisticated in their decision-making capabilities. These executives explained that they are seeking the right mix of mind and machine to understand risk and make predictions to model the future. The timing is right for insights teams to make an entrance. Traditionally relegated to number crunching and reporting, data scientists have become more valuable in the age of #BigData. They are the closest to the analytics and can help to drive innovation in insights, but to do so, they have to gain a seat at the leadership table.
Airbnb recognized the importance of giving insights a seat at the executive table at the launch of the business. The head of data science was one of the first 10 Airbnb employees, and every leadership team in the company has data scientists on board. Insights leaders bring the right mix of human judgment and machine learning to the strategy discussion that can help to nurture creativity and collaboration and keep the company competitive.
Data Scientists leading the way
By gaining a seat at the leadership table, the insights team can better drive innovation across the organization. Data scientists can insert themselves into the discussions that move the company forward by:
- Providing more insights. Don’t just report the data, insert context around the insights being shared. Data scientists are closest to the information and often have a unique point of view that may encourage a different way of interpreting the numbers.
- Being the MVP (and Ask Questions). Follow up with executive leadership to gauge how reporting is being received. Ask questions to determine if more insight is needed and strive to make the analytics team an MVP within the organization.
- Changing the culture. Lead the effort to move from a silo culture to a collaborative organization by expanding the sharing of data and analytics reporting beyond the executive team. Engage with finance, marketing and sales, for example, to provide valuable “did you know?” insights that can improve their departments or programs. By opening the insights team up to other stakeholders in the company, this encourages collaboration, and these departments can become the biggest cheerleaders and supporters of integrating insights more deeply into the company.
- Employing the best technology. The mix of human insight and machine learning is the best approach for developing effective analytics to support a high-performing enterprise. Identify and integrate analytics that examines beyond historical data to focus on predictive analytics for modeling the future. The ability to provide reporting that anticipates, rather than reacts, is more valuable for decision making.
- Becoming a master communicator. According to Riley Newman, Airbnb’s head of data science, qualities that make the difference between a good versus great data scientist are soft skills, including communication, creativity, and curiosity. If this is an area of weakness, professional development and practice make perfect. The ability to relate and translate complex data into an understandable and actionable discussion with company leadership will increase the insights team’s value.
To learn more about Prevedere’s predictive analytics capabilities, check out the webinar recap Sharpen Business Performance with Predictive Analytics.