When streaming music service Spotify listed on the New York Stock Exchange in April 2018, it was valued at about $30 billion — even though it doesn’t own what it sells, has never turned a profit and isn’t expected to for years. Spotify is a digital disruptor that is upending an established business model, a digitalization dynamic playing out across industries. Increasingly, the challenge for CFOs and finance leaders is how to keep up with businesses that need to transform dramatically and at high speed.
The shift to digital business requires finance to reconsider its design and mission
“Digitalization requires finance to re-evaluate the value it provides to the organization, how it delivers that value, its stakeholder relationships and the capabilities the function needs,” says Tim Raiswell, principal research leader at Gartner. “To keep up with digital business initiatives, finance must deliver value at a faster pace and in a different way.”
Digital future of finance
In its primary mandate of governing and reporting, finance continues to improve performance. Most finance functions have embraced technologies such as electronic transaction processing, spreadsheets, financial enterprise resource planning (ERP) systems and planning tools. Many are evaluating emerging technologies such as robotics and artificial intelligence (AI) and analytics to further improve.
“Finance has embraced digital tools, but the shift to digital business requires finance to reconsider its design and mission,” says Jason Boldt, research director at Gartner.
The digital shift will manifest in four key areas:
- Value model: To create data and expertise as a service from guiding managers to make financially informed decisions.
- System for delivering value: To continuous, integrated processes and flexible support from calendar-based processes and project-aligned support
- Capabilities: To product- and data-engineer capabilities from accountancy and analyst-based
- Stakeholder relationships: To distributed and multidisciplinary from matrixed business partnerships
These shifts will occur as finance reconsiders what it means — and what it takes — to guide decision makers in the digital age. Traditionally, finance produced financial information and taught others how to use it to make better decisions and judgments. Often, financial data was the most valuable, and sometimes the only, source of information for organizational decision making. That is no longer the case.
Plug into unstructured data
Summarized financial data, long used for decision making, is now insufficient. It can be misleading because it is typically only a weekly or monthly snapshot of performance. Consider, for example, a restaurant chain that is testing microstrategies for adding new menu items, parking spaces or drive-through lanes. A summarized report might hide the behavioral shifts that reveal customer preferences and — more importantly — which behaviors are most profitable.
Leading finance teams will become digital interfaces for their organization’s financial data
The business now has a wealth of information to inform its understanding of environmental, social, and other behaviors and dynamics that affect key business indicators like customer profitability. Consider the many unstructured big data sources in the figure below. The challenge for finance is how to properly reconcile that big data with transactional financial data.
“The value of the finance function in a digital business rests on how well it can underpin and power enterprise applications with financial data, without a person in between,” says Raiswell.
“Leading finance teams will become digital interfaces for their organization’s financial data, allowing both analysts and digital tools to ‘plug into’ it. This role will enable profitable and efficient growth decisions, no matter how micro or localized.”
Digitalization has a far-faster cadence than traditional business models, so no finance function or business can afford slow-moving models of analyst intervention. Finance will need to use many different types of financial data — for example, forward-looking data that can help forecast the profitability of a transformed business model. This data will need to be immediately accessible and easy to manipulate, or finance won’t use it.