Without doubt, the financial planning and analysis (FP&A) role has attracted much deserved attention over the past decade. There is also no doubt that business intelligence (BI) and analytics are key tools for substantially enhancing the impact of the FP&A team on overall enterprise performance and economic results. This raises the question – what BI and analytics skills do FP&A professionals need to optimise their impact?
BI and Analytics – Essential Skills for FP&A Professionals?
Typical BI applications leverage business data to produce:
- Multi-dimensional analyses.
- User-defined queries.
- Scorecards and dashboards.
- Advanced analytics.
- Predictive analytics.
Using BI can enhance FP&A activities such as planning; forecasting; budgeting; controlling; variance analysis; scenario analysis; communicating goals and results; and decision support. A recent American Productivity and Quality Centre (APQC) research report, entitled ‘The Seven Essential Qualities of a Winning Financial Planning and Analysis Professional’, noted that two of the qualities have to do with BI and analytics, these being:
- Mastery of systems, analytical tools, and data management.
- Ability to design reports and self-service tools that business managers will use.
Skills in BI and analytics are a pre-requisite for advancing the efficiency and effectiveness of FP&A teams. Having these skills within the FP&A team enables acceleration of the pace at which data warehouses, BI and analytics can be deployed, which is often hampered by IT priorities, processes, and economic objectives. It is also slowed for FP&A because many companies invest first in BI and analytics for sales, marketing, customer service and operations. This need not be the case if the FP&A team has the skills to drive enterprise use of BI and analytics.
In many companies, the FP&A team and the primary business units operate in ‘shadow IT’ modes. The FP&A team often obtains data from the company’s many business systems, manages it in Excel or in packaged FP&A software, and then uses it for its various business purposes. At the same time, business units are doing the same thing. This creates competing versions of ‘business reality’ – due to different ways of obtaining data, different analytical assumptions, and different definitions of business terminology and performance metrics. It is also inefficient – and sometimes ineffective.
The Skill Set
Companies overcome these challenges by building data warehouses and data marts for cross-functional use. These data repositories are then ‘hooked up’ to packaged BI and analytics software packages, or platforms that enable the use of common business facts for cross-functional and/or business unit BI and analytics applications. The skills for doing so on an enterprise or business unit basis are many, including:
- Business domain expertise; for example supply chain, sales, operations, FP&A, etc.
- Knowledge of data architecture, database structures, and database design.
- Ability to analyse and document the structure and meaning of data within company business systems.
- Skill using data profiling/quality tools to assess data quality and its suitability for specific BI applications.
- Ability to identify and document business requirements for information; for example, forecasting, customer segmentation, variance analysis, capacity planning, etc.
- Knowledge of the different types of BI and analytics.
- Data modelling skills, including entity-relationship modelling and multi-dimensional modelling.
- Ability to use extract, transformation and loading tools to obtain data from business systems and move it to data warehouses and data marts.
- Database administration skills.
- Software and database testing skills.
- BI and analytics application development skills.
Today, all but the business domain expertise are considered IT skills. In many cases, acquiring such skills requires specialised education and training. Many of the professionals with such skills have at least an undergraduate degree in fields such as management information systems, systems engineering or computer science. Accordingly, it seems that most FP&A professionals would need to have more ‘systems’ training than is common in order to achieve mastery of systems and data management.
That said, many FP&A professionals are proficient in using Excel and Access to import data from business systems, and many are skilled in using reporting, BI, and analytics software. The challenge, it seems, would lie in expecting FP&A professionals to build data warehouses and data marts to best practices standards within an FP&A shadow IT environment.
Moreover, it is realistic to augment traditional FP&A education with BI and analytics training that prepares FP&A professionals to lead the charge when it comes to enterprise adoption of BI and analytics, and to serve as BI and analytics requirements analysts, application developers, and power users. Modern, efficient financial planning and analysis requires financial data, operational data and the BI and analytical tools to leverage that data. The FP&A team can play a huge role in enterprise adoption of BI and analytics- if it has the drive and skill to do so.
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