In the information age, data is everything. With our ability to store swathes of that binary gold, and to pull it from scores of different sources, we have access to more information than ever before. What’s more, by using analytical tools, we can blend datasets and create rich insights that were previously impossible to do (or at least incredibly arduous!).

At the heart of this data utopia is the premise that data is ‘great’; if we’re not measuring something, then we’re missing out. After all, data tells the ‘truth’…right?

Well actually, that depends on what you mean by ‘truth’. After all, the ‘truth’ can be subjective and open to interpretation – and the same goes for data; the conclusions you draw from your data ultimately depend upon what you’re looking at and how you’re looking at it.

Have a roadmap before embarking on your data analysis

An important consideration when working with data is that the quality of your output is wholly dependent on the quality of the planning at the start – specifically the aims of any analytical outputs.

Having a clear roadmap for the aims of your analysis in the first instance is important in providing direction for the project, allowing you to ask the right questions of your data and draw on the appropriate data sets. There’s a lot of information out there and it’s easy to find yourself in a sinking quagmire of data sources that bear little relevance to your intended analysis.

Whilst scoping the aims of a data analysis project may seem daunting, there are three simple steps that you can follow to ensure you give yourself the best hope of arriving at a meaningful outcome:

  1. Decide on a purpose – what, in a general sense, is it that you’re trying to achieve with any analysis.
  2. Pitch to the right audience – Who is going to consume the data? It may be at many levels of seniority (from Analysts to Executives), and each will require and expect different things.
  3. Define the questions to be answered (and then the supplementary questions that arise from that) – these are not just the pure data questions but rather the business question – i.e. the reasons for conducting the analysis in the first place.

Leverage your data in innovative ways

With the above three areas documented and the data acquired, the next step is the exciting bit – making the data work for you to answer your questions.

Again, there are three considerations to bear in mind for making the most your data:

  • Create quality data visualisations
    Choose your visualisations carefully and with the audience and questions to be answered in mind. Data visualisation, as with all visual communication, requires thought and discipline to present data in the most meaningful way (don’t just include a bubble or other fancy charts because it looks nice – it needs more justification than that).
  • Make sure the data has context
    Bring in those external metrics that help you make sense of the data. Having worked with data for my entire career it’s fair to say I’ve seen good data, bad data and everything in between. With bad data (and anything short of ‘good’) you’re going to struggle to get any ‘truth’ from your analysis – remember, “garbage in, garbage out”. However, one of the trends that I’ve noticed more and more is that even with good data people are quick to justify it – reaching for a readily accessible context; and that’s normally the context of their business or organisation.

This is context, and context can take many forms. It could be measuring your procurement against a commodity index or allowing for the impact of currency fluctuations, or indeed measuring against many others.

  • Blend your procurement data for greater insight
    Data is an incredibly valuable resource for any procurement team and its wider organisation. By pooling your internal data for spend, sourcing, contracts and projects (to name a few) and combining that with external metrics and benchmarks, you suddenly open up another level of insight into your data. Better yet, that insight can then be used to inform strategy across the organisation, increasing efficiency, improving savings and identifying opportunities for further innovation that yields yet more value for your organisation.

“If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” 

Jim Barksdale, former CEO of Netscape.

In the digital era, every procurement team has access to an invaluable source of strategic insight in the form of its data. By using technology to prod and probe that data, Procurement has the means to draw informed action plans that deliver innovation and value to the function and, more importantly the wider organisation. However, knowing the research questions to ask of your data and applying the right context to it is essential to realising this potential.

If you are interested in learning more about the kind of questions you need to be asking when looking to gain greater insight from your data, then please register for our free webinar, Innovative Data Leveraging for Procurement Analysis, on the 28th March. In it, distinguished US professor, Dr Robert Handfield will be taking a more in-depth look at pooling datasets to perform innovative procurement data analysis.