The Big Data revolution presents a unique opportunity for all businesses and CFOs need to be at the heart of it. Big data has been described as being like teenage sex: everyone talks about it, nobody really knows how to do it, and everyone thinks everyone else is doing it, so everyone claims that they are doing it too.
There are many definitions of Big Data so I will define Big Data, then look at ways Big Data can drive profit improvement, look at ways you can drive profit improvement then finish with a vision for the future.
I lived and worked in California fifteen years ago when the data revolution was beginning at the end of the dot.com bubble. People were thinking about how to better use all the data being created and the analytical power available was enabling new solutions and companies. Data was coming from digitisation of process steps, more (and digital) channels, and new technology.
As we know it today, Big Data as a term began being used in 1999. Studies found that in 1999, the world produced about 1.5 exabytes of unique information, or about 250 megabytes for every man, woman, and child on earth.
Big Data is first of allbig. The volume of information is growing at 59% annually. There were 14.7 exabytes of new information in 2008, nearly triple that volume of information in 2003. By 2020, analysts estimate that businesses will have 300 times more data available to them than they do today.
The accepted definition of Big Data is all about the three V’s: volume, velocity and variety. For example, every 60 seconds there are:
- 100,000 tweets
- 11 million instant messages
- 1,820 TB of data created
For finance teams, Big Data is also happening. Companies as a whole, and finance teams in particular are required to hold more data for compliance with anti-bribery legislation; Solvency II; and Environmental and sustainability reporting.
This is in addition, to the more ‘established’ areas of Big Data, in marketing and customer insight. Social media, blogs and websites are creating more data about your products and your company. Listed companies are required to report faster. The old adage that marketing teams knew that half their marketing was wasted, but not which half, is increasingly outdated – Big Data leads directly to far more selective marketing investments, with far more insight around the ROI of each.
Big Data impacts across the whole of your company. CFOs are best placed to be the overall coordinators for Big Data, and best placed to lead initiatives that will impact profitability.
How can Big Data help CFOs specifically to drive measurable profit improvement?
According to Ernst & Young, companies that have their arms around data outperform their peers by up to 20%. CFOs are making use of Big Data for a broad range of uses, for example:
- Forecasting: the combination of unstructured social analytics and financial forecasting is leading to a new generation of forecasting techniques in which forecasts are informed by customer sentiment about products, customers, and campaigns. The integration of Big Data brings new inputs and variables that help anticipate the future, enabling rolling views of leading indicators rather than more traditional retrospective views. More frequent inputs allow the enterprise to respond more quickly to change. While CMOs are using Big Data and analytics to better understand the individual customer, CFOs are utilising data to better understand the environment.
- Advanced financial and management analytics CFOs are used to dealing with highly structured and verifiable data – Big Data isn’t like that and it requires a change in mindset for CFOs to feel comfortable making use of it themselves. Many CFOs are driving business agility by analysing performance metrics such as resource productivity and inventory turnover. They are using this data to better understand their businesses and re-engineer and integrate business processes as part of a broader enterprise transformation.
- Minimising risk and fraud by continuously sifting through the details of every event and transaction seeking the often-subtle signatures of fraud or some other business risk factor. A recent survey of CFOs’ had fraud analysis as the top project, indeed the American SEC are now employing Big Data techniques to help regulate firms in the US. Banks use Big Data to call you up when there is an unusual spend profile on your account.
- Profitability modelling and optimisation with advanced cost analysis, product/customer profitability and allocations.
From a CFO perspective, Big Data is not just about new types of data; it is also about harnessing the availability of existing data. Business analytics tools enhance access while removing manual activity and enabling the processing of large volumes of data to make new connections and accelerate decision making.
In addition, CFOs’ need to be leading Big Data as Big Data will also be a big cost for companies: nearly 50% of Big Data project users detailed in a 2013 study were business stakeholders from marketing, finance and customer care departments. This is companywide transformation, not limited to either IT or marketing. CFOs’ will be at the heart of it.
It’s been said that you know when you have Big Data when your IT department spends more time purchasing storage capacity than making sure the business has the data they need!
International surveys have identified IT as one of the top three trends for the accountancy profession. Four in 10 of the US and UK senior finance executives quizzed by American Express are planning to increase IT spending in 2014 by at least 10 percent. Only 17 percent think budgets will stay flat.
The theme of getting more out of data attracts overwhelming support among CFOs, with 95 percent of them agreeing that their organisation needs to do more.
What data to use
CFOs can make use of data from social media sites and online forums, and we see this in areas such as regulatory compliance, supply chain and labour climate. They monitor formal and informal media to predict sales trends and understand investor sentiment.
CFOs are also starting to generate their own big data by instrumenting their businesses to collect and incorporate large volumes of performance data supporting their new challenges of driving strategy and growth.
A vision for the future
The applications of Big Data are only constrained by your imagination. I personally think the applications for forecasting and budgeting are really interesting – think about when the budget was done for most companies’ month 12, often more than 20 months previously.
However, one of the most interesting areas is cost and profitability. In most companies information on external expenditure, which is typically more than 50% of a company’s costs is backward looking, often inconsistently categorised and not integrated with internal costs.
Only 25% of procurement groups have visibility into contract compliance rates; fewer have visibility into supplier performance.
Finance and procurement teams have solved the first generation problem of viewing and understanding their spend. However, I often meet with CFOs who still say they do not know how much they spend on software (now that software is bought by every department) or they do not know how much they spend on categories like print or recruitment. Few can be sure that they are buying goods and services at the best cost, even among the suppliers that they deal with.
The next stage, therefore, is to combine historic spend information with:
- Price and cost of historic prices paid and prices offered
- Internal cost information
- Supplier performance information
- Revenue forecast information
News and environmental information
Third-party data will also become increasingly available to participants of the different business networks. The data may be generated by other network participants (i.e. ratings, feedback, payment history, etc.) or from third-party solution and information service providers who have partnered with the networks to deliver more, better, and more timely information to the network members.
With this information companies will be able to see and action in real time key factors that can result in lower costs for the business, and be better able to respond.
For example, areas where this Big Data approach can really make a difference include:
- Understanding who is the best placed supplier for commodity items or services
- Maybe the exchange rate has changed and it is now more cost effective to buy your new desktop computers in the UK rather than Europe
- When fuel prices have changed and it is better to consolidate volume
- When a part of your business is forecasting a large increase in demand.
- Logistics costs could get more expensive per unit, but a new supplier can be sourced to increase capacity
- Additional demand can be accurately calculated as new discount thresholds are reached for key inputs
- Supply can be assured for the volume increases
- When commodity prices are expected to change
- Production can be optimised to ensure that the unit cost increases do not impact production costs
I have worked on these issues for my entire career. However, Big Data approaches give us the tools and capability to be able to do it in real time and forward looking, rather than retrospectively. It is one of the most exciting developments of the last 20 years in cost and accounting.
I would encourage everyone to lead the development of Big Data in your companies and to use it to drive profit improvement.