ICAS research delves into the benefits of Big Data

Big Data

Big Data isn’t just for huge corporations. But how does a senior finance professional in a medium-size organisation acquire the skills they need? An ICAS-backed research project by Dr Alessandro Merendino, QMUL, and Professor Maureen Meadows, Coventry University, shows the way

1. Adopt proof-of-concept cases and learn from existing use cases

If you’re at an early stage of your adoption journey, start small. Use proof-of-concept activities to show the viability of Big Data – high-volume, high-velocity and high-variety information – and its value for the business. It’s helpful to consider use cases from both your own and other organisations to learn about new applications of Big Data, and successful and unsuccessful practices in the community.

2. Build Big Data literacy

Critical thinking and creative thinking skills are essential tools as your organisation adopts new approaches based on Big Data. Bespoke literacy training for senior finance professionals can help make the shift towards a data-driven culture. This can combine good practices and experiences of other senior figures both inside and outside the organisation. It could include training in how to interpret Big Data analysis; ensuring access to experts, within and from outside the finance team, and unpacking case studies on successful projects.

3. Build awareness of Big Data and its strategic potential

Big Data is often viewed as a specialist theme for data analysts, rather than an asset for the whole organisation, including the finance team. Treating it as a cross-cutting topic can drive improvement in the finance team’s performance. Make data strategy and data governance part of the organisational strategy. Link any positive impacts of initiatives to KPIs to encourage the C-suite to pursue Big Data investments.

4. Focus on the insights and benefits

Adopt a more forward-looking approach to encourage finance teams to capitalise on the newly available data and technology. The senior team can use tools such as scenario planning to gain insights into the future opportunities afforded by Big Data.

5. Establish metrics, KPIs and budget lines that show the value of Big Data

Embed Big Data analytics within the organisation’s KPIs. It can inform the creation of value for the finance team and the organisation. Establish a budget line for investments in infrastructure, and treat Big Data as an asset rather than a liability. Create a communication plan to explain its costs, benefits and the return on investment for the finance team and the whole organisation.

6. Take an experimental and flexible approach

Improve your understanding of Big Data by adopting a trial-and-error approach. Use case studies from successful projects (ideally in a finance/accounting context) as evidence to educate and persuade senior professionals who are curious about the benefits and want to learn more.

7. Build strong connections across functional silos

A “silo effect” can hinder the acquisition of Big Data capabilities. Set up a data working group involving senior staff across the organisation as a starting point for the finance team to learn and share ideas with other teams.

8. Identify and fill skills gaps

Run an audit exercise within the finance team and across the organisation. Identify any gaps in capabilities at the senior level, including the board or C-suite. Write an upskilling plan, identifying the actions required to fill Big Data skills gaps. This can include training existing staff, hiring new staff with the right skills or outsourcing certain roles.

9. Run workshops and networking events, internal and external

Senior professionals can learn from finance teams in other organisations, including practical examples of beneficial Big Data initiatives. Internally, the C-suite can meet to share their data needs and capabilities. These exercises can inform a comprehensive Big Data plan, to build awareness at a senior level of its role in creating value and improving performance.

10. Set up executive coaching and mentoring programmes

Coaching programmes designed for senior leaders can include sessions on the Big Data journeys of other organisations. They can cover how to create an environment that supports Big Data, and provides opportunities to share its challenges and aspirations. Coaching is likely to be short term and performance-driven, while a mentoring programme may be more long term and development-focused.

A series of videos has been produced to delve deeper into the findings from this research project. Watch the first video below and the full series here