Harness data from finance to create sustainable business advantage

The concept of “data-driven finance” is emerging as a key enabler for finance functions to develop more agile operations and reposition from being thought of as a cost center to a strategic partner and a trusted advisor to the business. HFS recently conducted a research study on data-driven finance surveying 207 senior finance executives, supported by data analytics and digital operations and solutions company EXL. At a recent HFS digital roundtable in partnership with EXL, we discussed the study’s key findings with a diverse mix of 21 finance executives.

Talent, data, culture, and legacy systems are common obstacles holding back finance from becoming data-driven

It does not come as a surprise that the top two initiatives for finance leaders in our finance and accounting (F&A) research study in Exhibit 1 revolve around talent and data. Hiring and retaining talent persists as the Achilles’ Heel of many organizations. Further, the lack of centralized data governance prevents finance leaders from achieving their digital transformation goals. Most of the finance leaders attending the HFS roundtable emphasized the need for identifying and resolving talent and data issues as central to becoming a data-driven finance function.

Exhibit 1: Lack of talent and decentralized data are the top challenges for finance

Sample: 2022 survey, 207 finance and accounting executives, data less than 1% not shown
Source: HFS Research, 2022

Our delegates offered a wealth of stories of their challenges and experience with tackling them during the sessions. The following themes resonated strongly within the discussion.

#1. Lack of skilled finance talent

Although finance is the custodian of organization-wide data, they lack the skills to transform the data into forward-looking business insights. Further, fueling the talent challenge is the scarcity of this highly skilled talent.

Potential solutions discussed at the roundtable:

• Create cross-functional finance teams of data, tech, and AI.
• Provide career mapping for talent retention.
• Use LinkedIn Learning for the self-upskilling of employees.
• Recruit talent from new-age schools and better cost geography.

#2. Decentralization of data and data quality

Everything generates data; consequently, data has become the new corporate asset, and finance is the engine that generates the data. The key challenge is how to build the framework to mine this “gold” to generate insights.

Potential solutions discussed at the roundtable:

• Implement quality control of underlying data.
• Use data lakes as a single source.
• Build proof points with smaller data sets.
• Set up finance data hubs.

#3. Lack of support for change management

Finance’s resistance to moving from spreadsheets and a transactional mindset to agile methods of working has slowed the progress of the function going beyond cost and compliance enforcers.

Potential solutions discussed at the roundtable:

• Champion inclusivity, training, and education.
• Communicate and collaborate.
• Share a purpose and vision.

#4. Spaghetti of legacy systems

Most organizations are buried under a history of acquisitions and legacy backbone systems that impede the adoption of modern operating models to become data driven.

Potential solutions discussed at the roundtable:

• Cloudify data assets and systems.
• Engage third-party service providers.
• Leverage a broader partner ecosystem.

Best practices adopted by finance leaders to move the needle towards data-driven finance

The HFS study revealed that most finance organizations are still in the “early innings” of their journey toward becoming data-driven, and fewer than 1 in 4 consider themselves mature.

Exhibit 2: Only 25% of finance leaders claim they have achieved maturity in data-driven finance and are looking to more strategic uses of data

Sample: 2022 survey, 207 finance and accounting executives, data less than 1% not shown
Source: HFS Research, 2022

A quick poll of the organizations at the roundtable revealed a result similar to the study findings: only 18% considered themselves as having mature, data-driven finance functions. These were the recommendations from the roundtable attendees:

• Your insights are only going to be as good as your data quality. Finance data quality and governance are critical to capturing value through analytics, digital, and other transformative opportunities. Advanced analytics and other data-enabling technologies are just a means to an end. These non-discriminating tools lead to value-driven answers only if your data quality is good and can inspire trust and confidence across the organization. Data to fuel an organization’s strategic initiatives must be more than readily available; it should also be of high quality and relevance.

What keeps me up at night is getting quality data. All these different vectors like ESG and regulatory bodies are driving up the demand for quality data.

– Marie Myers, CFO, HP

• Ask the right questions to make data work for you instead of the other way around. Business leaders must clarify their most pressing issues or priorities before seeking to get their data house in order. With hard funds and time constraints, analytics exercises rarely pay off from vague questions. A sharp focus and defining a clear purpose statement before embarking on small incremental steps in the data journey will lead you to the results and opportunities that data is supposed to deliver.

Whenever we try to evolve on a data journey, the critical question I have always asked is, ‘What is the problem you’re looking to solve?’ You need proof that this is the right journey.

– CFO, business services group of a global retailer

• Build people and technology capabilities to bring alignment across the organization. Mature, data-driven finance organizations are investing in educating the teams on data and building data skillsets for the future. Empowering the organization through capability building around talent and technology will create capacity, allowing finance to be more than a cost center. Additionally, data and insights often live within department boundaries. To truly unlock their value, organizations must collapse their internal departmental silos and bring a single view to data.

[The] number one priority was educating the finance team. The second was around people capability building. We wanted our colleagues to not just be educated on how the data information flows, but what [they can] now do.

– Global Head of Finance Transformation, global pharma company

The Bottom Line: Start today! Small steps now will pave the way to achieving the goals of data-driven finance.

Across industries of all sizes and scales, there is a great realization that finance functions in organizations face similar challenges to becoming data driven. Organizations may be at different stages of evolution, but they are all on the same journey. The road to data-driven finance is complex and plagued with numerous challenges. While enterprises search for the right tools, technologies, and talent they need to thrive, forging ahead with small incremental steps is the path forward.

You need to start with whatever data access that we have today so we can derive those meaningful insights and start sharing that with the business.

– Narasimha Kini, EXL, EVP Global Business Leader