The Real World of Analytics Practitioners
“Dream big, start small, don’t waste time, and start now.” In one sentence, De Large Landen’s Vice President and Global Head of Analytics Teuni Breg provides both a sense of urgency and word of caution against “boiling the ocean” when integrating analytics into business decisions across the organization. Her comments were the highlight at the unveiling of a new research study by Dun & Bradstreet and Forbes Insights to a gathering of big data and analytics executives in New York City in June 2017.
Who is Using Business Analytics in for Decision Making
The study focuses on exploring the current state of analytics adoption across numerous use cases and industries. Researchers wanted to understand which companies perceive themselves as being “analytically driven enterprises” and better understand the challenges, pitfalls, and best practices associated with establishing analytics an integral part of business decision making.
“We use analytics to make more efficient decisions. In addition to finding faster, better, cheaper solutions, we use analytics to help manage the overall organization,” said event panelist Wagner Vagar of HSBC. His comments illustrated a common theme among the panel discussions. Individual analytics groups in key business functions are being asked to contribute across the organization. In a world where data scientists and analytics professionals are in high demand, companies are pooling and sharing scarce expertise and leveraging it across the enterprise.
Another event panelist, Andrew Koehler of Verizon, pointed out the difficulty in finding great people. “We're a team of about 50 people doing reporting, data management, and predictive and prescriptive analytics. Unfortunately, the predictive and prescriptive function is handled by about 15% of those people. We have about six or seven data scientists. After that, only half of our employees are doing models across finance, marketing, sales, and global operations, while the rest is being outsourced,” stated Koehler.
How Organizations Use Business Analytics
Many participants in the discussion pointed out that their analytics use cases stretch across the organization. Koehler highlighted his organization's use case growth. “Sales loves to hear from us, especially when we're providing a perspective on churn – predicting or revealing the risk of losing revenue or customers. In global ops, we're forecasting dispatch activities and trying to plan resources in different areas based on when we think we're going to anticipate dispatches. For our finance team, we are forecasting booked revenue results. I am trying to get them ahead of that gap at the end of the month when they're getting ready to report results. My goal is to help them anticipate what they might be seeing so they can get their messaging ready,” he said.
Chris Corinaldi of Fundation pointed out how analytics helps a start-up like his stay competitive. “Risk management historically was about minimizing losses. More and more, we're using data and analytics not so much for minimizing the losses and risks, but managing them within a certain level of tolerance. Even if you're a bank, you still have a validation obligation and perhaps a much tighter risk tolerance. We're also using data and analytics to help us aggressively grow the business within that tolerance,” stated Corinaldi.
How Finance Departments Are Using Analytics
Chief financial officers (CFOs) are looking to data to improve operational efficiencies in their departments and to help grow their businesses. Of those surveyed, 63% in the finance function said they are using data and analytics to find opportunities to fund business growth, showing that data is a primary driver in strategic planning for many enterprises. Driving home the strategic value of analytics, 60% of respondents said they use data to help drive long-term strategic planning.
When it comes to efficiency, 54% of those in finance look to data to help improve their organizations’ cash flow, showing that analytics is moving into more discrete finance functions like corporate treasury and cash management. Of the finance professionals surveyed, 53% said they look to analytics to help improve their operational efficiency.
How is Marketing Analytics Driving Customer Acquisition
When it comes to data and analytics, the number-one use case for chief marketing officers (CMOs) and their marketing teams is driving new customer acquisition, with 58% saying they are using data to find new customers while 55% use analytics to grow the number of leads they generate.
Another major use case for data in marketing is improving operational efficiency. The portion of those who said they look to data to drive efficiency and help cut costs in their departments was 53%, while 52% of those surveyed are looking to data to help improve the conversion of the leads they capture.
With all this emphasis on the value of data, it’s no surprise that CMOs and their teams are concerned with the quality of the data they use. As previously cited, only 42% of those surveyed in a marketing function had confidence in the quality of their data.
How Procurement Analytics Helps Supply Chain Risk Management
Chief procurement officers (CPOs) are looking to advanced analytics to drive their supply chains to greater levels of efficiency and cost control. According to the supply chain and analytics professionals we surveyed, 37% are using data to better understand their supplier spend. Roughly 33% are using analytics to manage financial risk among vendors. Drilling in more deeply, 32% are using this data to complete risk assessment for vendors below Tier 1, while 26% are analyzing risk for vendors at Tier 1.
When asked about desired outcomes, 60% of professionals working in procurement said increased efficiency and cost cutting were the most desired outcomes for use of data and analytics. However, only 35% of respondents said they are currently seeing the return on their drive for greater data-driven efficiency. Clearly, CPOs and their staffs have a longer way to go before they fully harness the potential of data.
Improved customer experience was cited by 45% of respondents as a desired outcome, with 49% stating that data is already helping them achieve these goals. An additional 45% noted improved brand value as a desired outcome for analytics, with 52% saying their data initiatives already help the other leading use case for procurement – improving tax performance. Tax optimization was listed by 44% of respondents as a desired outcome, with an almost equal 43% citing it as a result of their current data efforts.
Vagar closed the day with a comment that provided a qualitative observation that validated the findings of the research study. “I can say now, in our business, 100% of the decisions are really based on some level of analytics.”