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How private company CFOs can use data to make a difference

Implementing sophisticated data analytics can be challenging for private company CFOs, but the rewards can be great.

In brief

  • Compiling and using data analytics is essential for private companies to remain competitive.
  • Private company CFOs face the daunting task of organizing and using data.
  • Real-time insights can result in real-time actions that positively impact the bottom line.

For most organizations, sophisticated data analytics has become a critical tool for maintaining a competitive edge, and private companies are no exception. It is the CFO who is often tasked with leading the transition to advanced analytics; according to the latest EY DNA of the CFO survey, 35% of finance leaders in private companies are significantly involved in providing data analytics to reduce costs and improve effectiveness.

The potential rewards are great. Cloud storage, business intelligence systems and artificial intelligence (AI) can all bring insights from data, almost in real-time, with dramatic impacts on profit margins. But the task of organizing data can also be daunting for a private company CFO, with challenges that range from defending against cyberattacks to overcoming staff and cultural issues.

EY professionals spoke to three private company CFOs to find out how implementing data analytics had transformed their businesses.


Chapter 1

Cost savings and market insights

Using the cloud saves time and produces quick results.

Patrick O’Callaghan is CFO of Schuman Cheese, based in Fairfield, New Jersey. He is targeting a seven-digit cost savings through data analytics. “We can’t get there fast enough,” he says. “Now we’ve identified the leakage, we want to turn the faucet off and keep that margin in the business.”

The firm started its data analytics journey by moving existing data to a cloud storage system over the past three years. “That allows us to access data from anywhere, and to control, audit and track it better,” O’Callaghan explains. “This control is especially important when sharing data externally.”

Moving to the cloud produced an immediate cost savings. O’Callaghan was surprised to see that different groups had created around 30 inventory reports, with a lot of time and effort; creating one “cube” of information saved time for much of that activity.

Schuman Cheese then started procuring market intelligence such as point-of-sale data and uses a data dashboard and analytics program to scrutinize this information daily and provide insights into sales and margins.

The firm has also been moving to a new enterprise resource planning (ERP) system. “The availability of data reporting and analytics within the new ERP was a sizeable reason for selecting it,” says O’Callaghan. “We’ve also purchased a business intelligence platform from the same maker, so the two can integrate.”

For example, the COVID-19 pandemic sparked tremendous demand volatility. Analyzing foot traffic data helps us predict demand by looking at data spikes where customers are drawing down inventories, and how those might affect their orders to us. We can then tailor our inventories and raw material movements.

For Jennifer Crow, CFO of Austin, Texas-based AI software company, CognitiveScale, data analysis has helped revolutionize her firm’s route to market.

“Our investors and C-suite have an insatiable desire for more information,” she says. “Our team’s role is to narrow the data to metrics that can drive decisions or identify problems – such as those around customer acquisition, churn, and lifetime value. We combine information from different platforms into one scorecard, then compare our metrics with similar-sized companies. Customer metrics include net promoter scores, product use and renewal, customer churn, and cost to acquire new customers.

“The biggest thing this data has shown us is the best way to get new customers. Traditionally, we’ve used direct sales, which makes customers expensive to acquire. But, following insights from customer data, we’ve expanded our focus to partner with larger companies, which will reduce acquisition cost. It directs our focus by showing how much the relationships will benefit us long-term, improve sales velocity, and enable us to scale faster.”


Chapter 2

Uncovering opportunities

Insights provide value by reducing the cost of new sales.

Another positive outcome was seen in 2020, when CognitiveScale removed several business costs and Crow analyzed various data to monitor the effects. “It showed that we may have cut too much in sales and marketing, which slowed our selling cycle – so in 2021, we are reinvesting in that area,” she says.

After the 2008 financial crisis, many firms were accused of indiscriminate “top slicing” with insufficient analysis of good and bad costs, which sometimes hampered their recovery. Crow says that, post-pandemic, more sophisticated analytics can help companies make better-informed decisions.

Betul Sadikoglu, CFO, Eurasia at Wittur Elevator Components in Istanbul, Turkey, has also achieved some high-impact outcomes with data analysis.

Understanding business performance drivers and the company’s strategic direction allows you to define clear, aligned key performance indicators (KPIs). When you see any variance in KPI data, you can then look for negative drivers, and what tools might improve it.

To drive value and insight from data, Sadikoglu segmented the business around cost centers, created profit analyses for each, then developed a methodology for allocating overhead costs based on these analyses. “This has helped management understand margins and what drives performance in each segment, then decide whether the growth strategy in each is right and if not, how to reallocate resources,” she says, adding that she tracks indicators in each segment and in the company’s project pipeline weekly.

Internationally, Wittur Group focuses on selling elevator components such as doors. But in Turkey it had a different model, producing the full elevator system from manufacture to end customer.

“The Turkey business’s profitability was a hot topic when I joined the company,” says Sadikoglu. “It was thought to be low-profit and resource-hungry, and the group was challenging the worth of investing in it. But with my segmented analysis, I could show group management that Turkey was profitable, and even creating value and driving sales in other parts of the group.”

Like Schuman Cheese, Wittur is implementing a new ERP system across the group that will integrate business intelligence tools. This will enable faster reporting and make performance metrics in each entity more visible and easier to analyze, says Sadikoglu.

O’Callaghan expects his firm’s integrated business intelligence and ERP systems to unlock many more insights around product- and customer-level profitability. “It will dramatically enhance our pricing and promotion management, and enable us to flex volumes more accurately according to needs,” he says. “This will also save on areas like freight charges as our logistics team capture more information from the system.”


Chapter 3

Data challenges

Traditional thinking and cybersecurity concerns can be obstacles.

According to the EY CFO survey, the biggest barriers to finance driving sophisticated, real-time data analytics are: “a culture of reporting the past, not predicting the future” (25%); “lack of urgency, with decision-making weighted toward intuition over data” (23%); and “data security and privacy concerns” (23%).

Crow says automating as much of her finance function as possible has enabled her team to spend more time focusing on value-adding data analytics. One challenge is that the size of the organization currently limits its ability to invest in business intelligence, so it relies on its current ERP and manipulating spreadsheets for now.

O’Callaghan says careful implementation of data processes has enabled his function to evolve from “score-keeping” toward a culture of analysis and unlocking valuable insights. But size is also a challenge for Shuman Cheese in terms of finding sufficient resources to manage the processes and maintain staff buy-in.

“However, being smaller and private, all the key stakeholders are on board already,” he adds. “That enables us to transition more quickly than a larger organization with more bureaucracy. To ensure we had the necessary dedicated resources, we’ve hired people better suited for working with data as the workforce turned over. Training is also critical.”

To secure wider engagement, O’Callaghan worked with functional leaders to understand business drivers and how they work together. As the data project evolved, the team built a central database containing reports from all the functions, which fed into the analytics. “That helped open functional leaders’ eyes to the much larger amounts of information they can access,” he explains.

Schuman Cheese moved one staff member into a cybersecurity role, implemented a new cybersecurity service and may fortify it further with open source threat indicators. This action has helped to screen out attacks. But there is always a risk, so user education is also important, says O’Callaghan.

To address its concerns around cybersecurity, CognitiveScale appointed a director of information security five years ago. “He checks the whole security landscape and makes sure we do everything possible to avoid becoming the next victim,” says Crow. “I work closely with him, but it gives me comfort to have someone in that role.”

One challenge for CognitiveScale is that – because some of its developers and customers have different preferences – it uses three cloud providers. “There was initial reluctance to put financial information in the cloud, but it’s been seamless,” says Crow. “The cloud has allowed us to have more real-time information and to work smarter.”

Wittur’s data is also stored in the cloud across the group. “This is critical for managing IT infrastructure and security,” says Sadikoglu. “The cloud is protected by strong firewalls, but it is user-friendly and makes backing up data easier.” She adds that Wittur also works with an external hosting company, which provides cost efficiencies and standardization at the group level, and avoids the need to build an internal team.

For data hosting and management, Schuman Cheese uses an infrastructure-as-a-service model. This removes worries about managing infrastructure and enables the team to scale activity up or down as needed, says O’Callaghan. It also improves disaster recovery options.

The next stage of the journey has been to start using AI, with bots that collect information to improve customer enquiry responses. It is also planning to use more intelligent automation as it implements its new ERP. “We’re putting in a system that collects information from our manufacturing networks,” O’Callaghan explains. “An example is how fast the machine is cycling, to give us an idea of output. This will help identify failure points so we can improve manufacturing process efficiency.”

The initiatives all three firms have implemented show the range of data analytics applications that are now available. Such techniques are bringing valuable competitive advantages to nimble private companies that can implement them quickly.


Patrick O’Callaghan has 20 years’ experience in senior finance positions. He became CFO of Schuman Cheese in 2020 after joining as Vice President – Corporate Controller in 2014. Previously, he worked at World Finer Foods, Honeywell and American Express.

Betul Sadikoglu has 18 years’ experience in C-suite positions. She has been with Wittur Elevator Components since 2019 and previously worked at DowAksa Advanced Composites and Aksa Akrilik.

Jennifer Crow has nine years’ experience as a CFO and has been with CognitiveScale since 2019. Previously, she worked at WellAware Holdings, Asure Software and Active Power.


Private company CFOs need to use data to unlock valuable insights that can create competitive advantages for their businesses.

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