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    Procurement Analytics 101: Beginner's Guide 2023

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    • SudhaData & BI Addict
      When you theorize before data - Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.
    10-November-2022
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    • Procurement
    • Data Management
    • Data Science

    Editor's Note: Procurement analytics involves the gathering and examination of procurement data to obtain valuable business insights and facilitate informed decision-making. Leveraging this beginner’s guide, understand the benefits and value provided by Procurement Analytics with detailed Procurement use cases and key terms definitions.

    Introduction

    Call data the “new oil” or the “new water” it doesn’t matter. Because whatever the comparison might be even “air”,everyone knows it is omnipresent and important for organizations. That is also the case for Procurement. Once you realize how crucial data can be to create value, all it takes is one step toward the data journey in procurement. So take that first step by understanding what Procurement Analytics is, what value it provides, and some use cases for analytics in procurement.

    What is Procurement Analytics

    Procurement Analytics is the process of collecting, cleansing and analyzing the data from procurement for insights and decision-making. Sounds easy? Let’s take a small recap about the multiple types of data that are available with procurement - Supplier data, Cost per item, channel data, spend per category, savings, procurement policy data, etc., and this is just the tip of the iceberg.

    Procurement data which is collected from multiple sources and data systems are generally disjointed and distributed across various systems making it difficult to be analyzed. All this data is then stored, effectively cleaned, and classified to be used as per business needs or per-use cases.

    Let’s understand in detail some of the challenges procurement analytics has and the multiple types of use cases wherein users can understand the value it creates.

    Challenges for Procurement Analytics

    A 2021 Deloitte's Global CPO survey found that CPOs' priorities have dramatically shifted over the last few years. For nearly 78% of them driving operational efficiency tops the agenda instead of cost-cutting. One of the key ways to achieve this is with Procurement Analytics. This shows that most companies are interested in implementing analytics but are unable to do so. Some of the reasons might be:

    • Non-standardized procurement processes across business units
    • Lack of integration across various technologies
    • Lack of synchronization between metrics to be tracked
    • Absence of uniform data across organizations for better negotiation
    • Inefficient cost and payment tracking

    You might be wondering why we have spoken about the challenges first rather than getting into the examples, and the use cases of procurement analytics, it is because once you understand what the problem is it is easier to identify the solution.

    Key Procurement Terms

    Before we get into understanding the benefits and the value that Procurement analytics provides, it might be helpful to understand some key terms for those who are not familiar with the topic. If not feel free to skip to the next section.

    Sourcing

    Sourcing is the process of identifying needs, managing suppliers, and fulfilling the said needs to fulfill resource requirements that organizations need on a day-to-day basis. It involves strategy, research, and evaluation. It is more about assessing, selecting, and managing the suppliers i.e. the supplier relationships. Though this is often confused with Procurement, it can be considered a part of overall procurement.

    Procurement

    Procurement is an end-to-end process that deals with sourcing i.e. finding the suppliers to payment including planning, negotiating, managing inventory, issuing purchase orders, etc. Organizations use procurement data to evaluate vendors, identify cost-reduction opportunities, reduce contract and sourcing time, etc. It can be divided into strategic and transactional procurement.

    Source-to-Pay

    The process of end-to-end procurement is commonly referred to as the Source-to-Pay cycle or S2P cycle, it is further divided into two parts- S2C and P2P cycles. Source to Pay includes the entire process right from sourcing the vendors/suppliers to paying them after the delivery of goods is complete.

    Source to Contract

    This part of the Source-to-Pay cycle called Source-to-contract includes functions like sourcing, supplier management, contract management, and category management. It deals with identifying the right suppliers and maintaining a relationship with them.

    Purchase to Pay

    This part of the Source-to-Pay cycle called Purchase-to-Pay includes Purchase order management, invoice management, purchasing, and payment management. This cycle is more about fulfilling the requirements raised by the team when it is needed.

    Spend Analytics

    This term is one of the most commonly known use cases of Procurement Analytics. Spend analytics or Spend analysis refers to the analysis of spending data from multiple sources like invoice analysis per category, purchase order analytics to understand the cycle times or supplier management, and payment term analytics for identifying any deviations or scope for improvement. We’ll be discussing more on spend analytics below.

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    What Are The Four Different Types of Procurement Analysis?

    Like any other analytics function, Procurement can also be divided into descriptive, diagnostic, predictive, and prescriptive analytics based on how the users want the data to be analyzed. In case you are new to the subject:

    Descriptive analytics: Use historical data to find out “what happened”, some use cases include classification, clustering, and regression analysis

    Diagnostic analytics: This is about using statistical methods to identify “why something happened”, techniques including time-series analysis, ROI calculation, channel analytics for best platforms, etc., techniques would depend on the use case needed.

    Predictive analytics: Finding patterns in data to help forecast situations for effective decision-making in the future. Some examples include root-cause analysis, market basket analysis, demand forecasting, etc.

    Prescriptive analytics: Taking a step further to analyze multiple scenarios and identify likelihoods. For example, this can involve analyzing multiple vendor data for the best cost savings or optimized time.

    Though most organizations determine the level of analytics maturity needed based on the above four types, there is one more way to decide on the procurement analytics processes i.e. based on who is going to use or how it is going to be used.

    Operational Analytics: Analyzing metrics that are needed for day-to-day operations like cycle times, status, pending orders, etc.

    Financial Analytics: Metrics about the financial effectiveness like cash flow analytics, impact on P&L, etc.

    Strategic Analytics: KPIs that analyze strategic processes to stay compliant with organizational policies

    This categorization is important when the organization might have different levels of analytics requirements for their different departments or business units. Unsure about the level of analytics needed or business needs for implementation? Don’t worry, our Data discovery workshop can help you with the same.

    Procurement Analytics Data Sources

    Some of the data sources that would be involved in the entire STP cycle, which would be useful for analysis are Master data with products and users

    • Payment-related data
    • Supplier data
    • Sourcing data
    • Contracts data
    • Invoicing and Goods data

    Understanding where all the data is and collating them forms the first step even before the analysis comes into the picture. Therefore, if you are looking to analyze your procurement data, then it is important to understand the various data sources and integrate them with master data. Now, let’s talk about some of the key use cases of procurement analytics.

    Procurement Analytics Use Cases

    Procurement as a function has been growing over the years, and with the current advancements in technology right from data management to business intelligence, the maturity level of analytics has been increasing from reactive to proactive. As such, it is important to know some of the key use cases to understand how to meet the increasing needs.

    Analyze Supplier Performance

    Create detailed dashboards or matrices to analyze supplier performance with various metrics and KPIs like the process to arrival time, risk analysis, sustainability performance and social responsibility of each of the suppliers, CO2 analysis, etc. With transactional and strategic reporting about the suppliers, you can identify delays, manage current inventory, and reduce bottlenecks.

    Improve procure-to-pay cycle time

    The procure-to-pay cycle involves all the transactional activities right from benchmarking to payment. Therefore, KPIs like speed to market, demand fulfillment rates, procurement efficiency, etc., can be identified. This process allows you to connect multiple departments together and prevent data isolation to prevent bottlenecks. Internal operations and trends can be identified for reducing effective procurement time.

    Detailed Spend Analytics for cost savings

    Spend analytics as mentioned above, is the study of the spend across categories, geographies, SKUs, and products. With effective spend analytics, multiple categories can be analyzed if any organization has other suppliers who are offering similar products or services at lower rates in other business units. You can also analyze historical pricing trends, benchmark against other competitors, payment term analysis, and invoicing data analysis. Spend forecasting is another advanced branch of spend analytics wherein you can study the impact of spending on profitability.

    Realize greater savings

    You can affect your bottom line and create effective savings with techniques like effective price variance analysis, supplier base rationalization, category analysis, and rogue spending. Effective procurement strategies with data backing can help you create new areas where procurement might be needed as opposed to previous sourcing, therefore reducing wasteful spending. Future shifts in needs can also be identified for reducing costs.

    Mitigate procurement risk

    Though data forms an integral part of the entire procurement cycle, the P2P cycle deals with quantitative data for cycle time, and STC data deals with procurement management data where supplier risks and contractual conditions are of paramount importance. You can reduce sourcing risk by analyzing supplier performance and checking adherence to norms. According to research by Deloitte, only 18% of CPOs were tracking risks in their Tier-1 supplier base.

    Contract Analytics

    Many people think that once a contract is signed it doesn’t need any more analysis, if you are one of them you are wrong, as contracts are a vital part of the entire vendor relationship. Terms in the contract like payment, renewal, expiry, deliverables, etc., are extremely important for understanding the performance and the product terms. Some products over time would need a change in the contract terms based on the strategic importance, as such keeping track and request for change would be beneficial for both the vendor and businesses. Analytics can also help you manage contract expirations with timely alerts for the same.

    Overall, Procurement analytics can help you answer questions like:

    • What categories have the largest spending?
    • What is the deliverability of goods and services?
    • Are there any delays in payments?
    • Is there any variation across suppliers for the same good?
    • What is the average time of the entire STP cycle?
    • Any key outliers in the suppliers across business units?
    • Any suppliers that the business has bottlenecks with or is over-reliant on?
    • Is the business taking advantage of seasonal discounts?
    • .. and more.

    Benefits and Value of Procurement Analytics

    Now that you’ve understood the various use cases of procurement analytics, let’s sum them up into shorter benefits and the value that it adds to your business. Analytics touches on a lot of aspects of the entire source-to-pay process. Some of the key areas are cost modeling, bid analytics, contracting analytics, transactional analytics, spend tracking, etc., making it very important to be understood.


    use cases of procurement analytics

    Source: Accenture

    The benefits of procurement analytics can be seen once they are implemented. Some organizations can see savings from minor procurement strategic changes like streamlining all the product sourcing from suppliers.

    • Identification of savings opportunities by optimizing suppliers
    • Analytics in Sustainability and corporate social responsibility
    • Analytics in profit and loss reporting for finance
    • Analytics in risk management for suppliers and mitigation
    • Contractual management analytics

    These are the top few benefits of analytics in addition to spending analytics, which we have discussed quite a few times above.

    In conclusion

    Most CPOs now understand the importance of analytics but are stuck about where to begin or how to proceed. This is where our procurement analytics experts can help you with. With our detailed data discovery workshop, maturity assessment, and expert discussions we can help your organization with your procurement analytics implementation and adoption. If you’re interested fill in your form today.

    About Author

    procurement data analytics
    Sudha

    Loves to write and talk about everything data

    When you theorize before data - Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.

    Generally Talks About

    • Procurement
    • Data Management
    • Data Science

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