Cutting spend waste using AI

In the next generation of spend analytics technology, artificial intelligence will help to solve a number of very tangible problems

By Stefan Foryszewski, Executive Vice-President at Tungsten 

With an increase in tuition fees, UK universities have found themselves under constant scrutiny as to how they spend their money. On top of this, the Department for Business, Innovation and Skills has announced further funding cuts to be made, with an extra £450 million pulled from universities. These two factors have led to increased pressure on universities to not only watch what they spend but also look at ways to further cut costs.  

With students paying a premium to attend university, the expectation to get ‘bang for their buck’ has intensified, with some universities finding themselves in the firing line. Social media provides the perfect outlet for disgruntled students to voice their opinion and vice-chancellors are becoming increasingly aware of this. 

While £9,000 is a significant sum for students to pay, for most universities the student fees only make up a small contribution towards overall overheads like funding research, investing in up to date facilities and general running costs of multiple buildings. In most cases staff salaries make the largest dent in university outgoings, with staff to student ratios being a top priority for most education-focused establishments.  

‘In recent years software has become available to help procurement departments identify where cost savings can be made and the technology is now coming of age and reaching new levels of sophistication.’

With this in mind, running a university is no different to running a very large business and vice-chancellors will be looking at ways to cut costs and reduce their overheads without compromising resources dedicated to student learning. In recent years software has become available to help procurement departments identify where cost savings can be made and the technology is now coming of age and reaching new levels of sophistication.

As an electronic invoicing provider, we recognised the opportunity to provide detailed analysis for our customers by using existing data collated through our platform and have since developed complimentary, and indeed revolutionary, technology, such as our spend analytics function.

Analysing spend means we can provide our customers with a wealth of data and insight into their spending and invoicing habits by highlighting opportunities to save them time and money. For universities this could be anything from whiteboards, to computers to temporary staff costs.

Intelligent computing and data analysis has uses across the business world and major global firms are taking notice. Google and Facebook are investing heavily in research and development in these areas, while Amazon Web Services has set up a dedicated Machine Learning team.

In addition, Tungsten Network has partnered with Goldsmiths University to develop its spend analytics capabilities further, through which it has set up the Tungsten Centre for Intelligent Data Analytics (“TCIDA”). TCIDA is to undertake research and development into advanced Artificial Intelligent (“AI”) techniques for undertaking “Big Data” analysis.

The term artificial intelligence brings to mind science fiction, but in the next generation of spend analytics technology it will help to solve a number of very tangible problems.

AI helps computers understand and interpret written text. Machines can’t read so they need a way to identify semantics. For example, if two product descriptions are written in slightly different ways, say ‘25 notebooks’ versus ‘notebooks 25’, artificial intelligence helps a computer to interpret these as being the same thing.

Next, spend analytics will be further developed to learn functional equivalence. For example, a person would know that a Ford and a Nissan are both car brands, but a computer wouldn’t know that unless it was told.  The next generation of spend analytics will see computers programmed to learn these subtle differences to improve the analysis. Finally, we can expect the technology to evolve to achieve greater levels of trend analysis, using financial modelling to predict future pricing patterns and assess supply chain risks.

In vital public sectors like education, cutting costs while maintaining the expected level of services can often seem impossible. This is where spend analytics comes into its own. By analysing spend and looking at ways to save on smaller expenses like pens, stationery or laptops, we can ensure that our public education organisations are run as efficiently as possible, leaving more money in the pot for developing new courses and attracting the highest quality teachers.