There’s no denying that business intelligence and analytics emerge at the top of the lists of every CIO’s technology investment priorities. In a time where all the big checks are directed to the CFO, the office of finance clearly understands that leaders throughout their companies need the competitive advantage of technology that helps them manage the business more effectively.
Progressive CFOs are showing more interest in the value of analytics and business intelligence solutions for the functions they directly manage. They recognise that the ability to utilise data for a wide range of analytical tasks can help them balance the demands of financial and risk management in a volatile business environment.
Yet even these finance executives still have questions about why traditional technologies are even necessary. In my experience even when finance leaders appreciate the conceptual value of transforming their approach to data and analytics, they still want help with the following insights:
What are the leaders doing?
A study by The Hackett Group showed that world-class companies have a higher level of standardisation, but they use 10.2 fewer finance applications per $1 billion in revenue than other companies. The same study also showed that world-class companies produce 781 fewer business performance reports per $1 billion in revenue than other companies.
The study proved that, while complexity does impede standardisation efforts, most complexity is actually self-imposed. High quality, targeted information leads to more efficient and effective decision making. This is just one of many data points indicating that leading companies are already embracing an integrated finance foundation to stand out from the crowd.
What are the challenges of building a finance foundation?
Despite the potential benefits, it can be difficult to move to a data-driven, multi-dimensional finance model thanks to:
- Rapidly increasing volumes of stored data with no common definitions
- Lack of industry standards
- Changes in business software
- Difficulty deciding which BI tools and data marts should be decommissioned or revamped
- Poor data quality that prolongs time-to-value
To overcome these obstacles, finance leaders along with all relevant stakeholders – from finance, IT, BI, and line of business management groups – should plan in advance on how they will overcome these challenges. It might be helpful to read up on similar size companies who have tackled comparable challenges.
How do we get started?
First, ask peers who have already traveled the path to point you toward potential technology and services partners with the ability and experience to overcome these challenges and help you best utilise and understand all of your data. Success also requires a very strong CFO department that can spell out and follow a set of guiding principles including simplification, standardisation and consolidation.
Equipped with such expertise and focus, you will be well equipped to perform these key initial steps:
- Define how you want to view and analyse profitability
- Identify who’s asking for profitability analyses, and how they are using them
- Document and validate business requirements
- Create a functional definition of the profitability model
- Conduct a detailed data assessment
- Develop and prioritise a roadmap
- Approve the roadmap and start small
- Create a logical data model
- Develop calculations and business rules
An effort that is sometimes viewed as too all-encompassing to be practical becomes much more feasible when it’s broken down into a clear list of steps such as these. By following the proven path toward establishment of a fully integrated finance analytic foundation, including the related multi-dimensional insight into your company’s profitability, Finance and IT organisations can team to provide analytic capabilities that empower the C-suite and make a measurable contribution to improved company performance.