How optimising data can improve IT buying decisions

Procurement data drawn from multiple sources can also help businesses avoid locking themselves into sub-optimal technology contracts and missing out on the latest innovations.

The adoption of processes that use procurement data to its full potential is a major transformation project that can be daunting for any procurement team, particularly those working in the fast-moving world of IT, which is a sector that lags behind an already sluggish industry-wide move into the realm of digital procurement. However, the process can be broken down to create a targeted and effective solution that can deliver a real return on investment.

Current limitations

Like every activity in any modern business, the purchase of IT services and systems generates data. However, there is real variation between businesses as to the volume and granularity of that data and the extent to which it is retained for future use.

Whilst pricing information is generally kept on file, data such as a comparative analysis of each bidder’s approach to volume discounts or their commitments to ’net zero’ emissions targets are less likely to be held for future use. As the procurement world adopts an increasingly digital way of working, the absence of broader datasets that could be used to influence future procurements will become an increasingly important limiting factor.

Where strategic investment has been made in procurement teams over recent years, it has tended to focus on the implementation of e-procurement systems which aim to provide an end-to-end process starting with a business requirement and delivering a competitively tendered solution.

The challenges that exist in implementing those types of platform should never be underestimated. However, all too often, the resulting system streamlines and automates low level procurement processes, with any retained data tending to focus on the identity of the winning supplier and associated pricing models, with more detailed information being buried within an extensive library of tender material and associated email traffic. As a result, access to broader market analysis and lessons learned from a given procurement requires a time-consuming deep dive into an unstructured library of tender documentation and associated email exchanges.

When considering the extent to which procurement data is available to influence future buying decisions, this type of e-procurement solution could be classed as ‘Level 1’, in the following three level hierarchy:

There are a number of disadvantages of operating at Level 1:

• Over-reliance on some individuals – market knowledge in relation to a given procurement category sits with one person and is lost when that person moves to a different company or retires;
• Repetition of past mistakes – when a supply arrangement is re-procured three or five years after it was originally created, it is highly likely that core elements of the new procurement will evolve from existing arrangements, with inadequate regard for lessons learned previously;
• Tendency to extend sub-optimal contracts – lack of procurement bandwidth, strength of business relationships and an inability to easily identify potential savings means that the business case for running a new procurement or considering a new supplier is weak;
• Lack of innovation – new supply arrangements often create innovative thinking and associated savings, as well as greater flexibility to respond to disruptive events such as the Covid-19 pandemic.

There are likely to be few businesses that would not aspire to move to Level 2 or 3, but that aspiration will equally be tainted by concerns regarding the resources required to make that move and the short-term disruption that could result. However, breaking the process down into four steps can help to challenge this view:

• Analyse – identify and categorise current and projected IT spend;
• Focus – adopt a targeted approach. Spot those categories or sub-categories where spend is high; there are multiple potential suppliers; and procurements are planned in the short term.
• Demonstrate – achieve support and buy-in from strategic leads by operating a pilot that demonstrates savings and return on investment.
• Implement – use the evidence of the pilot to generate policy and broader support.

Even with those elements in place, any initiative must have data at its heart and ideally that data should be drawn from as many sources as possible. Relevant data sources could include:

• Own systems – historical data relating to current and past suppliers, focusing on price but where possible also considering items such as service scope and service quality;
• Market information – direction of technology change and practice in the procuring entity’s sector;
• Trusted third parties – performance information published by independent third parties;
• Regulators – information published by regulators entrusted with the investigation of regulatory breaches and associated enforcement action.

Wherever the data comes from, issues will arise in relation to the validation of data inputs, the rapid ageing of data and any potential breach of confidentiality obligations associated with data use. The best way of overcoming many of those constraints is to use licensed information that is supported by warranties applicable to the data’s scope and accuracy, recognising that access to data of the right quality will come at a price. 

If budget is available to support implementation of an IT procurement data project, thought should be given to engaging one of the growing number of firms that specialise in delivering projects of this type, through the provision of consultancy services and/or software tools. Having access to relevant legal advice is also important to ensure that procurement processes, template contracts and project-specific agreements allow the capture and use of relevant supplier information to support a procurement function that is re-aligned so that data analysis is a fundamental input to all buying decisions.