Big data and finance in cultural attractions

For the chief financial officers of the world’s cultural attractions, big opportunities lie in unlocking the hidden value behind the venue’s data. The challenge is especially relevant as analytics technologies transition from reporting on the venue’s own history into predicting future performance.  Forecasting with big data analytics offers financial executives and their leadership teams greater surety in the venue’s ability to hit target, a distilled capability for communicating on target performance to the museum team and an early warning system to intervene with improvements while the game is still in play, rather than waiting to quarter or year end.

It’s all part of the modern financial officer’s balancing act of being a good steward and good strategist – a “bean sprouter, not just a bean counter” as Jeff Thompson, Forbes’ writer for CFO insights, puts it. Big data is the proving to be the weapon of choice for a ‘new breed’ of finance leaders trading  reporting and compliance for active business advisory responsibilities in a dynamic environment, with a need to remain up to the minute in order to form an evidenced opinion.

Outside the museum or other cultural attractions, financial officers worldwide are gearing up for the challenge big data presents to the finance function, equipping their departments with the skill sets, technology and habits to deliver meaningful insights for their own and their business units’ needs alike. The Wall Street Journal points out the natural fit for numerically literate finance teams with the challenges of learning and leading with business statistics, citing the American Institute of Certified Public Accountants that accountants are “perfectly suited to take a leadership role in deciphering and using big data to achieve strategic business goals”. This is particularly relevant in the arts, where many curatorial or public programming departments may have more of a natural affinity for traditionally qualitative measures.

It begs the question of who owns the analytics initiative in the senior leadership team. In the wider commercial sector, the chief financial officer sits in the top most common executive sponsors, alongside marketing and digital technology. In the cultural institution this is especially important given the director’s propensity to look to their finance function for analysis and advisory, data operations and as an ambassador for the institute’s commercial objectives for admissions, retail and other revenues. It’s also more than likely that finance is responsible for metric heavy functions such as internal governance and reporting, endowment and grant compliance, board and external communications and the governance agenda, for which data privacy, security and sovereignty plays a growing emphasis.

In many arts organizations, this initiative has risen from optional innovation with leftover funds through to a strategic initiative in focus, aimed at delivering significant power to visitation, revenue and operational efficiency. It’s also proving to be a cornerstone of the finance and technology relationship as the two departments partner on the regulatory, security and innovation agenda to enable the wider museum.

For the chief financial officer, big data analytics will arguably be the museum’s most important new technology investment, offering direct benefit to the finance department. As the competitive landscape for grants, endowments and visitor attention forces museum attentions to commercial sustainability, the financial officer will be increasingly called upon to push an agenda across the wider museum team for more aggressive growth and lean operations, wrapped in an ability to communicate, enrich context and collaborate over data. Big data analytics provides a mechanism for museum finance departments to:

  1. Alleviate the time and cost of manual reporting typical of museum management
  2. Collaborate with marketing and retail, exhibitions and experience on tweaking levers such as cost of customer acquisition and commercial conversion rate behind the growth conversion funnel of the museum’s business model
  3. Forecast, set key performance indicators and track progress to goals, creating a communication culture of transparency, evidence and accountability, such as the conversion for upsell admission to a special exhibition
  4. Evaluate, predict and monitor return on investment across the museum’s strategic initiative set in enabling the various business units of the museum, such as optimizing indoor positioning for a new in gallery digital interactive
  5. Address complexities for museum management around ticket price optimization, exhibition scenario modelling and commercial margins

The business case for analytics can be considered in two halves: quick win cost savings direct from annual data administration together with longer term enablement for increased revenues and decreased costs spread across various museum departments, such as optimizing front of house teams with more accurate forecasts, or improving average spend per visitor by lifting physical conversion into commercial spaces. Analytics also ticks other boxes inherent to the museum’s mission, such as achieving on social good outcomes, transparency and innovation.

Ultimately, big data analytics helps the museum drive cultural change to accountability and a discipline for return on investment, through data enriched collaboration. The new call to action objective for the chief financial officer will be in reducing ‘time to insight’, given experience suggests the less time teams spend administering data and producing reports, the more energy and passion they can dedicate to understand and act upon the insight data provides.