Build or buy your spend analysis solution for procurement

Every procurement organization needs to have visibility on their spend. There are many ways to do this. In one stream analysis can be done as desktop exercise in Excel, in another stream there are advanced analysis solutions that cater sophisticated needs of large enterprises. Procurement data can be dirty, scattered, requires plenty of attention and needs to be fresh, but is super valuable. In this article we will go through how to make best use of the mass of data in your hands.

Traditionally purchasing data was seen as a numerical byproduct of buying activities - it had no perceived value. Even though procurement data has been identified as an important business asset, relatively few organizations embrace it to provide a competitive advantage. By understanding past procurement performance we can guide future decision making.

We can use spend analysis to:

  • See what has happened in the past
  • Understand why something has happened in the past
  • Gain insights that support budgeting and management decision making
  • Use trends and patterns to forecast future business performance

The information gained from analyzing data is used to guide procurement category strategies, strategic sourcing projects, contract management and optimize the entire source-to-pay cycle. In addition to management insight, with data analysis companies have realized multi-million dollar savings opportunities. Organizations have come to realize that they need a procurement data strategy - and either make sense of the data themselves or partner up with a supplier that knows how to deal with their data.

Get your comprehensive guide to spend analytics: Spend Analysis 101

Defining a data strategy

Before you deep dive into data you need to define your data strategy based on your specific business challenges. One good starting point is mapping out all your data. In case of procurement data, there are multiple data sources and formats, which can be tricky to make sense at first. Examples of procurement data could include invoice data, contracts, supplier master data, p-card transactions and many more.

Creating a clear plan will provide direction on how you assemble, cleanse, store, manage and share the information for maximum benefit and profitability. Unstructured and unused data becomes an asset when it is combined, classified and analyzed. Like any plan it is not a one-off activity, circumstances change in dynamic procurement environments.

Why not put it on a spreadsheet then?

Data analysis can be done as spreadsheet exercise in Excel. Excel is a great tool for building dashboards that can provide analysis and deliver timely insights. While doing spend analysis on Excel is doable, most people will fail to do it efficiently and encounter issues. For example, Excel is not scalable for thousands to millions of rows of data. Challenges like over-generalized classification, data inconsistencies and formatting issues and same supplier with multiple names, cause inconsistency and result a normal analyst to do more cleaning than actual analysis. Even if you’re successful doing all this, it can take hours or even days of work. The same “update and classify” data crunching exercise is repeated each month, which will not be scalable without purpose-built tools for doing so.

As your organization grows, so does your store of data. Traditional, labor heavy procedures and manual systems will no longer be able to cope with the complexity and provide insights in the phase that its required. As there are solutions in the market that have sophisticated technology and service for spend analysis purpose alone – why not continue reading?

According to Deloitte CPO surveys (2020 & 2021) building a flexible and connected digital infrastructure with investments in advanced digital solutions are a critical enablers for success. High performing CPOs are 4-5 times more likely to have fully deployed advanced analytics, have fully deployed predictive analytics capabilities, and are 18 times more likely to have fully deployed AI/cognitive capabilities.

The build or buy decision

Before considering how to build or buy a procurement data solution you need to understand:

  • what data you have and what state it is in  
  • where data is stored and how it is accessed
  • how data is currently managed and governed
  • functional needs and level of customization of the solution
  • is there a solution available in the market that can fulfil those needs
  • is your team capable of developing a solution that can fulfil those needs
  • is your internal IT organization capable in supporting you in your needs

The decision of whether to develop an in-house IT solution (build) or source a solution externally (buy) is a never-ending debate. There are many pros and cons to both. There is no easy formula as every organization has different objectives and resources. Where an organization has both the financial resources and the advanced IT skills required, both build and buy are options that must be weighed up carefully.

Assuming there is already an appetite at senior level for a solution, there are three main issues to consider:

1. Total cost of solution ownership

Since procurement’s top priority is making savings, cost must be high on the agenda. The total cost of a proposed solution over its entire life cycle must be the basis for the calculation. Procurement teams apply Total-Cost-of-Ownership (TCO) principles to all key make-vs-buy projects, this is no different.

Most buy applications need integration with existing infrastructure and internal systems. When calculating the time expected to complete the entire project, specific time-consuming activities such as customization, changing work processes and retraining staff need to be costed and added.  

 Building a system internally means an IT team needs to use a platform such as Microsoft Power BI and continue to maintain it. The build cost includes technical training (if required) and direct labor costs but should exclude any fixed costs. The duration of an in-house built project is often longer due to the pressure of other IT priorities. Time is money and delays are expensive. Should your TCO calculation stand for “build” option, it makes sense to double-check if all related costs are taken into account and if the quality of in-house development and monthly upkeep is comparable to external solutions.

 

See below exemplary TCO comparison over a 3-year period.

 

Build buy TCO

Overall, the cost of the ”buy” should be less than the ”build”. This is due to vendors being able to utilize economies of scale and specialization, leading to lower unit costs. The attraction is often the offered subscription pricing model avoiding an upfront expense. The key here is to select and pay for only the functionality you need.

 

2. Criticality

How important is having an effective procurement data management system to the success of your business? The answer is very. Without usable historical spend data decision-making on future procurement is guesswork. System downtime is a risk, can an in-house system or external service provider guarantee that the system will be 99% available? Your stakeholders are likely very eager to make the most out of the vast mass of procurement data they have at hand, which means there is an urgency element involved.  Whether build or buy, the solution selected must meet all your specified criteria and be both secure and legally compliant.

 

3. Availability of skills

The choice of buy or build must consider how much technical skill and capacity is available internally and how mature the IT function is. In addition to technical skill, specific competence related to procurement landscape is required to understand how data can be best used as internal customers might face challenge getting across what they really need and what is possible solution-wise. Any skills upgrade project takes time and investment. Potential vendors of procurement analytics solutions are likely to have the knowledge and expertise available but are they relevant to your industry or business sector? Check for relevant customer testimonials and market reviews.

Presenting the business case  

Presenting the facts to senior management relating to cost, criticality and availability of skills are not the only considerations. The political and cultural environment within the organization has an influence. Organizational maturity in terms of data utilization plays its own part. There are known and unknown biases at play that influence the decision-making process. Prior experiences with a vendor, aggressive marketing by vendors and end-user preferences all play a part.

Maintenance and support

Whichever route is chosen the system will require security patches, bugs fixed, and new features added. An in-house build will depend on the development capabilities and capacity of existing IT staff, assuming that they are fully acquainted with market developments in procurement technologies. In-house team should understand how to classify and draw conclusions from the procurement data that best serves the end user requirements. Without that expertise, troubleshooting will have to rely on external community support. It could be said that an internal team has more control over planning changes and upgrades, thereby building confidence with stakeholders. Vendors have extensive technical analytics expertise and support teams for their products - this is built into the price.   A robust service level agreement (SLA) can ensure the quality of implementation, maintenance, and support – this applies equally to both build and buy solutions.

The keys to procurement data success

Technology alone will not deliver the results you are looking for. It is a tool that, in the right packaging with the right handling, can provide an easy-to-use-and-maintain system that delivers procurement value.

Keys to success:

  • Be reasonable in defining the scope of the project. Define what must be included now and create a road map of future additional features.
  • Secure an executive sponsor and confirm the budget.
  • Secure an IT sponsor to support with technical requirements.
  • Communicate the plan to stakeholders and end-users to ensure engagement and alignment with their needs.
  • Establish metrics to track its success.
  • Invest in change management to get most out of your new system.

The solution to the question - Buy or Build - may be a hybrid. There is no definitive answer. Buying a cloud-based software solution that is flexible, agile, and secure that can be integrated into your current platform can make sense on your data roadmap as your organizational maturity increases. Imperfect data can be valuable for dynamic procurement needs and can be enriched and combined with external data. Working with external partners can provide access to unique data streams and insights. It does not out-scope the possibility to add in-house developed modules as your needs demand and vary over time. 

At the end of the day, only no-value data is data that is not utilized. Your procurement data strategy and chosen solution is as unique as your business.

esteban-lopez-6yjAC0-OwkA-unsplash

Photos:

Yulia Matvienko @yuliamatvienko (picture 1)

Esteban Lopez @exxteban (picture 2)

Sources:

https://www2.deloitte.com/us/en/insights/topics/operations/chief-procurement-officer-cpo-survey.html

https://www2.deloitte.com/us/en/pages/operations/articles/procurement-strategy-2020-cpo-flash-survey.html

 

 

 

 

 

 

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