The role of the data and analytics driven CFO in the new world Big Data and Analytics
The data driven organisation is becoming the game changer for society. Similarly, the analytics and data driven CFO can be the game changer for your organisation.
Never before in recorded human history has it been possible to access massive amounts of data and information on demand – and from anywhere. However within established organisations, accessing business relevant, high integrity information on demand is a daily struggle.
This is where the analytics and data driven CFO can be a game changer for your organisation.
For CFOs still coming to grips with recent IT offerings such as Cloud computing and mobility, the new kid on the block is Big Data and analytics.
CFOs that primarily focus on the financial and accounting data face the challenge of coming to grips with enterprise data and information for three reasons:
- Most financial data is retrospective. While financial forecasting is stock in trade for the CFO, modelling the complex interactions between non-financial data to generate reliable forecasts is a different beast altogether
- The scope of data that CFOs in many organisations deal with on a daily basis are financial – operational data and information taxonomies for not financial data often do not exist or are ill defined.
- The accounting and other standards that apply to finance and accounting data are well established globally, are consistently applied and regularly audited to ensure compliance to legislated accounting standards.
Within most organizations, there is usually a significant amount of data locked away in various systems. Very few organisations have a fully defined, accurately maintained, enterprise-wide information taxonomy for all data. This is as a result of non-integrated systems, divisional silos, legacy technologies, Shadow IT as well as information accessed from outside the organisation, to mention but a few.
How does this relate to the data held within my organization, you ask?
Additionally, other than the core business systems (eg ERP) which contain the transactional data (accounting, invoice, inventory etc), unstructured data pervades every corner of most established organisation. This data includes items such as videos, images, emails, spreadsheets and Word documents – located on PCs, internal network servers, mobile devices, Google Apps, DropBox and other public cloud services. This presents a challenge in attempting to harness the potential business value in this data slum.
What’s the value in my organisation’s data ?
There are a couple of perspectives that can be taken on the potential value of the data within your organization:
- Value to You as a CFO: CFOs should be able to identify business value through better decision-making by taking an integrated, fresh perspective of your various data sources. That in turn could lead to improved risk management, better customer service and further innovation within the company. Simply put, joining the dots may not only prove to be a valuable exercise, it could potentially save your business through the timely access to the right information for the right reasons to arrive at the right decisions.
- Value to Others: In some instances, your suitably secured internal data, after its analyzed and anonymized, may be of more value to others than it is to you. This could drive new business opportunities. For example, could your customers’ buying patterns be of value to adjacent, non-competing organizations?
But it is only by taking a fresh perspective on the mix of your data that has been stitched together in a relevant manner, with other relevant data sources if needed, that its potential value will be realized. This will require effort, skill and diligence.
What? I’ve always been an analytics and data driven CFO !
The humble spreadsheet is the weapon of choice for most CFOs and their teams. Data manipulation and analytics are at the heart of what accounting and finance professionals do – and have been doing since the first computer – so what’s changed?
Enterprise IT departments have their origins in the processing of financial and back-office data back in the 1950s and 60s. Historically IT was known as the EDP (Electronic Data Processing) Department . So CFOs and finance teams were the early adopters of technology.
However, the 2D world of the traditional finance and accounting data is a far cry from the modern, integrated data that underpins most established organisations.
Enter the role of Data Science – the game changer for data and analytics driven organisations
Data science in an emerging discipline, and one that is crucial to resolving complex data problems that relate to transforming data into knowledge and information. Essentially, a modern day form of alchemy – turning base metals into gold.
Data science is the result of drawing together a range of specialised skills to work on data, and is not necessarily a job description. These skills include applied mathematics and statistics, computer science, pattern recognition, machine learning, natural language processing and operations research, to name but a few.
The specific application of your Big Data and analytics initiative would also require domain expertise. For example, if you are in the medical field, having a medical expert as part of the Big Data initiative should be a prerequisite. Same thing with finance.
The importance of an analytical and data driven CFO for your organisation
In this potentially complex data-rich business environment, the role that a capable data and analytics driven CFO is key to ensuring the end results are achieved.
Finance and accounting data is the ultimate common denominator of every organisation. It is this ability of every CFO to ensure the financial representation of key elements of all data taxonomies across and within the organisation is where the CFO comes into their own.
More importantly, the data and analytics driven CFO has the understanding, seniority and oversight of the organisation as a whole to ensure that their organisation’s key decision makers play their part in developing the multidisciplinary capabilities needed to ensure sustainable success of any analytics and big data initiative.