Spend Analytics

Use of spend analytics to drive your organisations transformation

10 min read
Akshay Upadhye
Co-Founder
Spend Analytics
5 min read

Use of spend analytics to drive your organisations transformation

Written by
Akshay Upadhye
Published on

Before we go into the core topic of this article, it is essential to ensure that we all have the same understanding of the meaning of spend analytics. Spend analysis is the process by which unstructured spend or invoice data, is converted into structured data and meaningful information that can subsequently provide executive management transparency.

spendkey dashboard

There are three core areas of spend analysis - visibility, analysis, and insight. By leveraging all three, companies can generate answers to the crucial questions affecting their spending, including:

  • Where is the money being spent?
  • Which 3rd party providers I am spending the money with?
  • What exactly I am buying?
  • How may I optimise the current landscape?

As per a report from Research and Markets, “The Spend Analytics Software Market was valued at USD 1.12 billion in 2019 and is expected to reach USD 3.05 billion by 2025, at a CAGR of 18.2% over the forecast period 2020-2025”. Another report from Data Bridge Market Research states that “Global spend analytics market is expected to rise to an estimated value of USD 5.66 billion by 2026, registering a healthy CAGR in the forecast period of 2019-2026”. As a result, it is no surprise that various organisations are coming up with strategies to restrict unwanted spending by adopting spend analytics software to analyse financial / spend / invoice data. The analytics platform also enables monitoring trends by integrating real-time data feeding.

Now the next question that may come in your mind is how can spend analytics drive any transformation? I think the answer is straight forward if we consider the following scenarios in any organisation and the application to spend analytics to fast track the process:

  1. Cost Out – As a CFO or another member of the executive management, you see costs rising. Therefore, there is an urgent need to make savings and free up working capital but don’t have the full visibility to understand where the cost-saving opportunities are quick. Spend analytics can come to your rescue to provide with that visibility to identify cost-saving opportunities!
  2. Shareholder returns optimisation – When investors trust your company with their hard-earned money, they would like to get attractive returns on their investments. Therefore, as an organisation, you need to gain the confidence to explore opportunities and maximise ROI.  Deploying a spend analytics platform can provide you with a a single source of the truth, helping you understand the underlying operating expenditure.
  3.  Strategy development – As part of your executive management team, you aim to develop your business, understand the client landscape and provide actionable strategic insights but you are faced with a heterogeneous landscape of ERP/ Finance/ P2P platforms and struggle to bring data under one hierarchy, then  intelligent spend analytics can be effective to classify your data into a structured taxonomy / hierarchy for decision making.
  4. Transformation – As a CIO or CTO, you have a task to identify opportunities and enable digital transformation; however, the stumbling block is that you do not have the visibility of the current state including critical suppliers, software products, etc. Getting an accurate view of your spend can help drive IT and digital transformation initiatives.
  5. Streamlining your supply – As a head of procurement, one of your biggest challenges would be to streamline your supply base, but the first hurdle is poor visibility of interdependencies and costs. To add to your problems, business owners do not feel accountable to terminate or consolidate suppliers. Building a category view to drive category strategies drives significant value to the organisation in such a scenario.

From real-life experiences, here are some recent examples of how spend analytics delivered significant benefits to various organisations of different types, sizes and complexities:

  • Ina leading UK financial services organisation, spend analytics highlighted several similar software platforms used for the same purpose by different departments/business units.  Once their CIO reviewed this information, the client created a business case for a  significant  software rationalisation programme. Not only it helped save the organisation some money on software license spend, but it also reduced the management overhead of maintaining multiple platforms.
  • In another organisation, once the CFO reviewed the operating expenses as provided by spend analytics, he realised that it wasn’t very profitable for a particular business unit to run with the current cost model; therefore, the CFO triggered a divestment initiative and sold off the business unit. Then pumped the money received from the divestment to deliver some significant digital transformation programmes to help the organisation gain competitive advantage and market share.
  • After getting output from the spend analytics platform, a large multinational manufacturing company realised that they were blocking significant cash every year to pay for the end-user device purchase as part of their 3-year refresh policy. The CPO explored the option of "device as a service" (DaaS),and the existing assets were sold to the DaaS provider at book value to free up cash for leveraged activities

To conclude, it is evident from experience that organisations will have increased demand for a more analytical and automated approach to managing their operational expenses (OPEX). With the ever-evolving technologies, features such as artificial intelligence (AI) and machine learning (ML) can effectively automate data scrubbing and data classification based on pre-defined taxonomy. But the critical point to note is that data analytics is not a one-time or periodic activity; more importantly, it is to review and analyse transactions in near real-time continuously. In this way, automation tools can identify spending behaviour patterns and deliver actionable insight to help guide the leadership team to take timely actions.

With Covid-19 acting as a catalyst for digital transformation, embracing data analytics as a tool to mitigate risk will be an essential part of organisations’ efforts to strengthen financial positions at a time when market volatility demands it. Spend analytics will no longer be a nice to have but a must-have capability for all organisations.

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Before we go into the core topic of this article, it is essential to ensure that we all have the same understanding of the meaning of spend analytics. Spend analysis is the process by which unstructured spend or invoice data, is converted into structured data and meaningful information that can subsequently provide executive management transparency.

spendkey dashboard

There are three core areas of spend analysis - visibility, analysis, and insight. By leveraging all three, companies can generate answers to the crucial questions affecting their spending, including:

  • Where is the money being spent?
  • Which 3rd party providers I am spending the money with?
  • What exactly I am buying?
  • How may I optimise the current landscape?

As per a report from Research and Markets, “The Spend Analytics Software Market was valued at USD 1.12 billion in 2019 and is expected to reach USD 3.05 billion by 2025, at a CAGR of 18.2% over the forecast period 2020-2025”. Another report from Data Bridge Market Research states that “Global spend analytics market is expected to rise to an estimated value of USD 5.66 billion by 2026, registering a healthy CAGR in the forecast period of 2019-2026”. As a result, it is no surprise that various organisations are coming up with strategies to restrict unwanted spending by adopting spend analytics software to analyse financial / spend / invoice data. The analytics platform also enables monitoring trends by integrating real-time data feeding.

Now the next question that may come in your mind is how can spend analytics drive any transformation? I think the answer is straight forward if we consider the following scenarios in any organisation and the application to spend analytics to fast track the process:

  1. Cost Out – As a CFO or another member of the executive management, you see costs rising. Therefore, there is an urgent need to make savings and free up working capital but don’t have the full visibility to understand where the cost-saving opportunities are quick. Spend analytics can come to your rescue to provide with that visibility to identify cost-saving opportunities!
  2. Shareholder returns optimisation – When investors trust your company with their hard-earned money, they would like to get attractive returns on their investments. Therefore, as an organisation, you need to gain the confidence to explore opportunities and maximise ROI.  Deploying a spend analytics platform can provide you with a a single source of the truth, helping you understand the underlying operating expenditure.
  3.  Strategy development – As part of your executive management team, you aim to develop your business, understand the client landscape and provide actionable strategic insights but you are faced with a heterogeneous landscape of ERP/ Finance/ P2P platforms and struggle to bring data under one hierarchy, then  intelligent spend analytics can be effective to classify your data into a structured taxonomy / hierarchy for decision making.
  4. Transformation – As a CIO or CTO, you have a task to identify opportunities and enable digital transformation; however, the stumbling block is that you do not have the visibility of the current state including critical suppliers, software products, etc. Getting an accurate view of your spend can help drive IT and digital transformation initiatives.
  5. Streamlining your supply – As a head of procurement, one of your biggest challenges would be to streamline your supply base, but the first hurdle is poor visibility of interdependencies and costs. To add to your problems, business owners do not feel accountable to terminate or consolidate suppliers. Building a category view to drive category strategies drives significant value to the organisation in such a scenario.

From real-life experiences, here are some recent examples of how spend analytics delivered significant benefits to various organisations of different types, sizes and complexities:

  • Ina leading UK financial services organisation, spend analytics highlighted several similar software platforms used for the same purpose by different departments/business units.  Once their CIO reviewed this information, the client created a business case for a  significant  software rationalisation programme. Not only it helped save the organisation some money on software license spend, but it also reduced the management overhead of maintaining multiple platforms.
  • In another organisation, once the CFO reviewed the operating expenses as provided by spend analytics, he realised that it wasn’t very profitable for a particular business unit to run with the current cost model; therefore, the CFO triggered a divestment initiative and sold off the business unit. Then pumped the money received from the divestment to deliver some significant digital transformation programmes to help the organisation gain competitive advantage and market share.
  • After getting output from the spend analytics platform, a large multinational manufacturing company realised that they were blocking significant cash every year to pay for the end-user device purchase as part of their 3-year refresh policy. The CPO explored the option of "device as a service" (DaaS),and the existing assets were sold to the DaaS provider at book value to free up cash for leveraged activities

To conclude, it is evident from experience that organisations will have increased demand for a more analytical and automated approach to managing their operational expenses (OPEX). With the ever-evolving technologies, features such as artificial intelligence (AI) and machine learning (ML) can effectively automate data scrubbing and data classification based on pre-defined taxonomy. But the critical point to note is that data analytics is not a one-time or periodic activity; more importantly, it is to review and analyse transactions in near real-time continuously. In this way, automation tools can identify spending behaviour patterns and deliver actionable insight to help guide the leadership team to take timely actions.

With Covid-19 acting as a catalyst for digital transformation, embracing data analytics as a tool to mitigate risk will be an essential part of organisations’ efforts to strengthen financial positions at a time when market volatility demands it. Spend analytics will no longer be a nice to have but a must-have capability for all organisations.

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Akshay Upadhye
Co-Founder
Akshay solves the biggest challenges faced by organizations as they digitally transform and establish a reputation for delivery. His contribution enables the business to realize a sustainable market competitive advantage, measured tangibly onto the business bottom line. His reputation is underpinned by a cumulative experience exceeding 22 years where he has been engaged by both small niche businesses to private equity-owned entities and world recognised brands.

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