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’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.
From a CPO and 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.
There are many areas where big data can help improve performance and profitability. 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 functions have visibility into contract compliance rates and fewer still have visibility into supplier performance.
Finance and procurement teams have solved the problem of viewing and understanding spend. However, I often meet with companies who still say they do not know how much they spend on, for example, software now that it is bought by almost every department, or they do not know how much they spend on categories such as print or recruitment.
Few can be sure 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:
Third-party data will also become increasingly available to participants of different business networks. The data may be generated by other network participants (i.e. ratings, feedback, payment history, etc) or from third-party solution providers.
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 improve responsiveness.
This approach could help when considering which is the best-placed supplier for commodity items or services. For example, if the exchange rate changes it may well be more cost-effective to buy new desktop computers in the UK rather than Europe and this data can help you understand this.
Another example would be if a part of your business forecast a large increase in demand. Logistics costs are suddenly rising per unit, but a new supplier could be sourced to increase capacity or additional demand could be accurately calculated as new discount thresholds are reached for key inputs.
I have worked on these issues for my entire career. However, big data approaches will give you the tools and capability to be able to do it in real time. To me, it is one of the biggest opportunities for procurement and finance in the past 25 years.
Ed Ainsworth is the co-founder and managing director of 4C Associates Ltd. He works with organisations on cost reduction, profit improvement and procurement.