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Welcome to the world of spend analysis, where every dollar holds untapped potential! In this guide, we will walk you through the secrets of successful spend analysis process and reveal why spend data is the ultimate game-changer for businesses of all sizes.
Spend analysis isn't just turning data into dollars, its about empowerment. It's about gaining visibility and insights needed to make bold, strategic decisions that pave way for your future success. By looking into spend patterns, you'll discover opportunities to streamline operations, cut costs, and build stronger supplier relationships.
Why keep reading? Spend data is not just a procurement buzzword - it's the cornerstone of your organization's financial landscape. In fact, it typically accounts for 60-80% of your turnover! That's why a savvy business leader knows that mastering the art of spend analysis provides keys to success in fast-paced, ever-evolving marketplaces.
Are you ready to unlock the potential of your spend data? Let's dive in and set you on the path to greatness!
Spend analysis is the process of evaluating an organization's expenditure data to understand spending patterns, identify cost-saving opportunities, improve efficiency, and optimize procurement strategies. Spend analysis aims to answer questions:
By analyzing products, prices, quantities, suppliers, business units, and payment terms, spend analysis provides a holistic understanding of spending patterns and supplier performance.
Here are some basic definitions and key concepts to get started.
Spend data (also known as procurement spend data) is information dealing with a company&#;s expenditures on goods and services purchased from external suppliers.
Spend data management is the process of collecting, sorting, and managing that spend data.
Spend analysis is the process of analyzing spend data to find patterns, identify cost-saving opportunities, improve performance, and optimize procurement strategies. It involves collecting, cleansing, classifying, and analyzing spend data from various sources to provide insights. The primary goal is to gain visibility into spending to make more informed procurement decisions and improve financial efficiency.
Spend Analytics, on the other hand, refers to the broader application of advanced data analytics techniques to expenditure data. While it includes the basic elements of spend analysis, spend analytics goes further by leveraging tools like artificial intelligence (AI), machine learning, and predictive modeling. This allows organizations to not only understand historical spending patterns but also to predict future spending trends, assess supplier risks, and uncover deeper insights that can drive strategic procurement decisions.
Spend analysis is a key component of effective financial management and procurement strategy building. This process helps Procurement identify areas of improvement and uncover potential savings by consolidating suppliers, negotiating better terms, and eliminating unnecessary expenses. By leveraging spend analysis, business leaders can make data-driven decisions that contribute to overall business performance and financial health.
Additionally, spend analysis enhances transparency and accountability, ensuring that all expenditures align with the company's strategic objectives and compliance requirements. By leveraging spend analysis, organizations can make data-driven decisions, optimize their procurement strategies, and achieve significant cost reductions, ultimately improving their bottom line and business performance.
Spend analysis offers procurement organizations several key benefits.
Here's an overview of some of the top benefits of spend analysis:
Improved visibility helps identify cost-saving opportunities . You can benchmark your suppliers, manage your tail spend, identify maverick buying behaviour, and ensure contract compliance.
Spend analysis helps you meet your cost reduction goals and also follow up on incremental savings initiatives.
Spend analysis provides better visibility and actionable intelligence. Gain a comprehensive understanding of spending patterns, leading to better financial planning and control. It gives you a comprehensive view of the metrics that drive improved cost savings, process efficiency, and supply-chain performance.
Spend visibility goes beyond tracking spending, as it gives both a detailed and holistic picture of how money is moving through your company. Having spend visibility allows for analyzing past spend which can be utilized for planning future direction.
By centralizing and organizing spend data, spend analysis minimizes the administrative workload associated with tracking and managing spend. There will be a significant reduction in cycle time for creating reports and ad-hoc analyses, reducing labor costs and freeing up time for more strategic work. By systematically analyzing spend data, organizations can quickly identify spend and sourcing opportunities. This rapid identification allows procurement teams to act fast, rather than spending extensive time manually combing through data to uncover these opportunities.
Spend analysis allows you to identify potential risks and ensure compliance with procurement policies and regulations. Analysis allows you to track and identify non-contracted spend and vendors. When your spend data is enriched with suppliers&#; credit scores and ESG information, you can better assess your organization's overall supply chain failure risk.
By analyzing spend data, organizations can evaluate supplier performance based on factors such as delivery times, quality of goods or services, and compliance with contract terms. This comprehensive evaluation helps identify top-performing suppliers and those that may require improvement. By benchmarking supplier performance against industry standards or other suppliers you set clear performance expectations and foster a culture of continuous improvement.
Spend analytics enables sourcing professionals to identify trends, market changes, performance issues, consolidation opportunities, and sourcing potential. It can be used to identify new sourcing categories, segment suppliers, and narrow down key suppliers for development programs. Companies can consolidate purchases with high-performing suppliers, negotiate better terms, and reduce reliance on underperforming ones.
Spend analysis allows you to leverage data-driven insights to make strategic decisions that align with your organization's goals and procurement strategy. Benchmark your performance internally across business units, locations, and categories to identify synergies and potential. Without timely data and holistic view of your supply chain performance, it's impossible to make decisions that result in the best outcome for your business.
While spend analysis projects vary in shape and size, they typically include six key steps from spend identification to analysis.
The first step is to get an overview of what spend will be covered. Doing this allows you to restrict those purchases to just a few key sources.
You can segment your spend into different groups and, from there, determine all the spend data sources available from your departments, plants, and business units. Start by identifying the areas of your business that make significant purchases, such as procurement, finance, and marketing.
Here are some of the most common sources of procurement spend data.
Once you have narrowed the scope down, you can capture your spend data and consolidate it into one central database. Data is usually in different formats, languages, and currencies, so collecting it into one source might be challenging.
Cleansing spend data detects inaccuracies and removes corrupt records and redundancies. This includes finding and eliminating errors and discrepancies in descriptions and transactions to ensure accuracy. Data cleansing lets you identify which contacts in your database are incomplete or irrelevant. Typos are removed, and missing codes are validated and corrected for up-to-date information.
Data enrichment refers to the process of enhancing, refining, and improving raw spend data. It also includes standardizing the spend data for easy viewing. Enriching the spend data makes sure that all the header and line-level names and details are accurate and to a specific naming standard.
Classification typically involves grouping several suppliers of the same parent company or organization. Unifying heterogeneous spend data into clearly defined categories makes spend easier to address and manage across the whole organization. Classification is about harmonizing all purchasing transactions to a single taxonomy, enabling procurement to gain visibility of the global spending to make better sourcing decisions.
Both direct and indirect procurement spend can be grouped into categories, enabling analysis and management of similar goods or services.
A spend category is the logical grouping of similar expenditure items or services that have been clearly defined on an organizational level. For example, &#;information technology&#; may be considered a spend category covering both IT software and hardware.
The spend taxonomy is the way a procurement organization classifies spend into hierarchies. One way to view spend categories is like a tree with many branches for different levels or sub-categories of spend.
The number of levels in a spend taxonomy depends on the procurement organization&#;s needs, ranging from three to six levels of categories and sub-categories.
When designing a taxonomy it needs to be thoroughly communicated and aligned internally with key stakeholders such as Finance and local/global Category Managers. A clear definition and understanding of each subcategory in the taxonomy helps in classifying your data accurately.
There are also standard taxonomies such as the UNSPSC (United Nations Standard Products and Services Code), a common coding system describing goods and services. It may be used to categorize procurement spend, but these are often not ideal for strategic sourcing.
The last step is to identify opportunities for savings and other procurement improvements. Analysis can answer business problems like "What are the best contract deals per supplier?" or "Are buyers purchasing from preferred suppliers?"
You can identify opportunities for reducing the number of suppliers per category and negotiating better rates.
If you've come this far, it is beneficial to consider how external data assets can provide deeper and more strategic enrichment to your analysis. By connecting 3rd party data to your spend, you can make more strategic decisions powered by data.
This is especially relevant in sustainable procurement. connecting Carbon emission data to your spend can help reduce your Scope 3 emissions. Supplier sustainability scores can also form a part of your category analysis.
Procurement data can be sliced and diced based on a number of key performance indicators (KPIs). Key Performance Indicators for spend analysis are essential metrics that help organizations measure the effectiveness of their procurement activities and identify areas for improvement.
Here are some crucial spend analysis KPIs to follow:
Spend Under Management: This KPI measures the percentage of total spend that is actively managed by the procurement team. High levels of spend under management indicate effective procurement practices and better control over expenditures.
Spend Visibility: This KPI assesses the extent to which an organization has a clear and comprehensive view of its spending data. High spend visibility enables better decision-making and spend management.
Cost Savings: This KPI tracks the total amount of money saved through cost reduction initiatives, such as supplier negotiations, strategic sourcing, and spend consolidation. It helps quantify the financial benefits of spend analysis.
Savings as a Percentage of Spend: This KPI measures the cost savings achieved as a proportion of total spend. It provides a clear indication of the efficiency and effectiveness of procurement strategies.
Spend by Category: This KPI breaks down spending into various categories, such as direct and indirect spend, to provide insights into where money is being allocated. It helps identify high-spend areas that may require closer scrutiny or optimization.
Supplier Consolidation: This KPI monitors the number of active suppliers and the concentration of spend among them. Effective supplier consolidation can lead to better pricing, stronger relationships, and simplified procurement management.
Supplier Performance: Metrics under this KPI include on-time delivery rates, order accuracy, and quality of goods or services. Monitoring supplier performance helps ensure that suppliers meet the organization's standards and contractual obligations.
Payment Terms Compliance: This KPI monitors adherence to agreed payment terms with suppliers. Timely payments help maintain good supplier relationships and can also leverage early payment discounts, contributing to overall cost savings.
Contract Compliance Rate: This KPI measures the percentage of spend that falls under negotiated contracts versus off-contract or maverick spend. High compliance or contract utilization rate indicate better procurement governance and cost management.
Procurement Cycle Time: This KPI tracks the average time taken to complete the procurement process from requisition to purchase order. Shorter cycle times reflect efficient procurement processes and quicker response to business needs.
Spend analytics solutions allow you to track KPIs in real-time through intuitive dashboards and custom reporting.
There are countless opportunities and insights to discover in your spend data. Here are 6 of the most fundamental procurement analytics exercises you can use.
The spend cube is a way to look at spend data projected as a multidimensional cube. The three dimensions of the spend cube are suppliers, corporate business units, and categories. The dimensions could include subcategories of the different units across the organization.
The spend cube is typically the &#;nal output of a spend analysis process. It allows you to look at all of the analyzed data from a variety of angles. A spend cube is usually needed if a company is not managing the full percentage of expenditures across all business units.
The 3 axes represent Category (What you are buying), Cost Center (Who you are buying it for), and Supplier (Who are you buying it from). These are the three legs of the stool &#; if any one leg is not there, the entire model falls apart.
Each axis of this cube contributes critical information:
Category analysis tells what specific types of goods and services you buy.
Cost center analysis reveals which functions (or end-users) within your organization drive the demand.
Supplier analysis tells you which suppliers you&#;re buying from.
You can then assess if expenditures are scattered or cumulative, or if suppliers have simultaneous contracts with different units in the organization.
You can slice and dice data to analyze it from many different directions. This ensures that you have just one sourcing strategy and not hundreds. You can base your category strategies based on more insights.
ABC Analysis
ABC spend analysis, also known as ABC classification, is a method used to categorize inventory or spending based on their importance to the organization. This technique helps prioritize management efforts and allocate resources by focusing on the most critical items.
Here&#;s how it works:
Supplier level spend analysis involves creating a detailed spend profile for each supplier using historical data. Supplier spend data gives enable year-on-year comparison and analysis for data-driven decisions.
Tail Spend Analysis
Tail spend is defined as the amount of money that an organization spends on purchases that make up majority of transactions but only a friction of total spend volume. In ABC analysis these fall into the category C.
Tail spend is generally considered low-value purchasing, as it makes up only a small portion of spend (usually 10% of each spend category). Tail spend is easy to ignore but it's often the area where organizations may be leaving money on the table and utilizing their resources inefficiently.
The figure above illustrates the simplest approach to analyzing a company&#;s tail spend: calculating the spend ratios to suppliers at various points along the purchasing range. Here, the Y-Axis represents spend per supplier ("Total Spend by Supplier"), and the X-Axis represents the total supplier base ("Supplier"). Suppliers are ranked in descending order.
Tail-end spend management has been growing in recognition and increasing importance within procurement. Tail spend analysis can yield potential savings, reduce costs, improve key supplier relationships, and increase spend under management.
There are usually many low-value transactions with multiple vendors across business units. To combat this, you can identify contract leakages and maverick spending. The aim of tail spend management is reducing number of suppliers and consolidation of spend to preferred or key suppliers.
Category spend analysis allows you to explore spend in a defined spend category hierarchy. This is useful in identifying spend leakage issues.
The first step in doing a category spend analysis is understanding the scope and breadth of the category. Are you buying similar goods and services from too many different vendors? This analysis is built on hierarchies, and the spend transactions are categorized into the most appropriate category.
Allocating spend consistently into categories makes the data easier to navigate, interpret, and understand. When organizations can focus on prioritizing their top spend categories, it helps them identify and forecast savings opportunities.
Prioritization will allow better negotiations for key spend categories to ensure more favorable contracts and pricing. By drilling into their spend data, procurement professionals are also gaining a deeper understanding of their spend categories.
When you have a high-level overview of spend by category, it is easier to identify categories that help deliver savings and realize which projects bring strategic importance to the organization. With this, you can easily figure out which action to take based on what has the most impact on staff or operations and what the risks associated are.
Item spend analysis refers to analyzing expenditure at an item/ SKU level. It focuses on individual purchases by classifying each one of them to identify what department it was for and what supplier was used.
This analysis gives the ability to know whether a specific item is being purchased from various suppliers or in several locations and at different item prices. It can highlight the different opportunities for purchasing in the business. You may also identify spend leakage issues, such as purchasing from non-preferred vendors and maverick spend.
Payment term spend analysis provides excellent insights for companies to analyze payment practices and terms within their purchase-to-pay (P2P) processes. It explores the opportunities of leveraging all possible discounts or interest from the invoice payment process while increasing working capital.
Payment term spend analysis gives a comprehensive view that enables you to identify unrealized payment term discounts, late payment interests, or opportunities to negotiate better payment terms.
It also covers the review of payment patterns to identify practices and activities that are not done properly.
Finally, contract spend analysis tells companies if they are complying with their existing negotiated contract terms.
It analyzes spending with vendors by contract to identify leakage through non-compliant contracts. It ensures that the best contract deals per supplier have been negotiated and that all buyers purchase from preferred suppliers.
Now that we have covered the spend analysis basics, it's time to look at the spend visualizations. Different data visualization types can help make complex spend analysis data more understandable and actionable, enabling organizations to identify trends, outliers, and opportunities for optimization more effectively.
Spend dashboard with bar chart, stacked bar chart, pie chart and line chart.
Here are most common procurement data visualization types and their use cases:
Bar charts are versatile and effective for comparing values across different categories.
They are commonly used to visualize spend by category, supplier, or business unit.
Stacked bar charts show the total value broken down into sub-categories, making them useful for comparing the composition of spending across different categories or suppliers.
Pie charts represent parts of a whole and are useful for showing the distribution of spend across different categories or suppliers.
They provide a clear visual representation of the proportion of spending in each category.
Line charts show trends over time and are useful for visualizing changes in spending patterns or supplier performance. They can help identify seasonal fluctuations or long-term trends in spending.
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Heat maps use color gradients to represent data values and are effective for highlighting areas of high or low spending. They can be used to visualize spend by geography, department, or other categorical variables.
Bubble charts represent data points as bubbles, with the size of the bubble indicating the value of the data point. They can be used to visualize spend by supplier, with larger bubbles representing higher spending.
Treemaps use nested rectangles to represent hierarchical data structures, making them useful for visualizing hierarchical relationships in spending data. They can be used to show spend by category, with larger rectangles representing higher spending categories.
Scatter plots visualize the relationship between two variables and are useful for identifying correlations or patterns in spending data. They can be used to visualize the relationship between spend and performance metrics such as supplier quality or delivery times.
Pareto charts combine both bar and line graphs to represent categorical data and their cumulative totals.
They are useful for identifying the most significant categories or suppliers contributing to total spend, highlighting the "80/20 rule" where a significant portion of spend comes from a small number of categories or suppliers.
Sankey diagrams visualize flow between nodes in a network, representing the magnitude of flow using the width of the lines.
They are useful for visualizing the flow of spending between different categories, suppliers, or business units, providing insights into how spending is distributed and transferred.
Waterfall charts illustrate the cumulative effect of sequential positive and negative values, showing how an initial value is affected by subsequent changes.
They are useful for visualizing changes in spending over time, such as the impact of cost-saving initiatives or changes in supplier contracts, by showing the net effect on total spend.
A spend analytics dashboard is a dashboard that visualizes sets of spend data into charts for the purpose of analysis. Datasets are selected based on predefined parameters, business targets, or KPIs.
The benefit of a dashboard is an instant high-level view of spending. In this chapter, we will cover some basic spend analysis dashboards used in Sievo.
A Spend Overview Dashboard provides an overview of your spend performance by comparing data of one selected period to the previous one. In the example, the view is filtered by year-to-date and presents the data by three four aspects: category, organization, supplier, and supplier count.
With a dashboard like this, you can track the top suppliers by region, spend changes by category, purchase process developments, as well as supplier count developments.
A proper spend analytics dashboard should be interactive, meaning you can select and filter data directly on the charts. Depending on what your responsibilities are, you can use a spend analytics dashboard to gain insights to questions or goals in mind with just one click.
A Supplier Performance Dashboard visualizes key data for a specified supplier, offering a 360-degree perspective. It highlights analytics on the top supplier by spend ranking, providing transparency into purchases and payment terms across business units.
This overview allows you to compare suppliers, identify performance opportunities, and strategize meetings for renegotiating or ensuring compliance with better payment terms.
The Category Performance Dashboard visualizes key data for a selected category, showing spend distribution, purchase order development, material price trends, and supplier sources. It offers valuable category management insights, helping to identify price opportunities, single-supplier risks, and track purchase order compliance. You can also drill down to assess purchase price developments at the lowest category level.
A Supplier Base Performance Dashboard lets you analyze your entire supplier base, track top and tail-spend suppliers, and identify consolidation opportunities to mitigate risks and create savings.
It is ideal for tail spend analysis and internal benchmarking, showing how fragmented or consolidated your supplier base is across different business units in a single category.
A Sourcing Performance Dashboard shows from which regions your business units are sourcing and whether materials are sourced internationally or domestically. It helps assess regional risks and anticipate the impact of trade or geopolitical issues.
This dashboard is useful for managing regional risks and identifying savings in logistics by switching to geographically closer suppliers.
A Process Performance Dashboard highlights improvement areas for small POs/invoices, revealing potential savings by identifying suppliers with small value transactions. It shows category differences in invoice/PO quantities and amounts, helping to spot discrepancies between business units or suppliers for process optimization.
This dashboard is useful for analyzing invoice and PO counts, benchmarking average values, and streamlining the purchase process.
A Price Performance Dashboard analyzes price differences among suppliers, helping identify opportunities for negotiation or finding cheaper options. It provides global and regional insights into price ranges within specified categories, aiding in price discovery and supplier selection. This dashboard is useful when you want to discover the price range of your specified category.
A Currency Performance Dashboard provides an overview of spend distribution in various currencies, highlighting categories or suppliers purchased using different currencies. It enhances transparency regarding risks, such as foreign exchange fluctuations. Filtering by category or supplier allows identification of materials or suppliers vulnerable to currency strengthening, aiding in proactive risk management.
The ready-made charts in the Sievo dashboards can give you a great overview with only one click. But what if you cannot find one matching your goal in mind?
What you will need is a Custom Dashboard, where you can mix and match any dimension, measure, and chart type for any report you need and slice and dice with any data point you want. This is especially useful for your presentations. The image below shows how Sievo's Self Service Craftboard allows you to build reports to meet your specific needs.
Example of Sievo&#;s Self Service Dashboard
There are many tools available for analyzing procurement spend ranging from simple Excel Spreadsheets to advanced analytics software. Here you can find the summary of the pros and cons of each alternative.
Excel remains a widely used tool for conducting spend analysis in many organizations. Its accessibility and familiarity make it a go-to choice for analyzing spend data. While Excel can be a useful tool for basic analysis, it has significant limitations when it comes to handling large datasets, handling advanced procurement analytics, maintaining data accuracy, and delivering comprehensive insights.
Small-medium size organisations may conduct relatively successful analysis in excel, but large enterprises looking to scale their procurement analytics and improve efficiency should consider investing in dedicated spend analysis software. Why so? Let's explore the pros and cons of using Excel for spend analysis in detail:
Excel is a readily available tool in almost every organization. Most procurement professionals are familiar with its interface and functionalities, making it easy to get started with spend analysis without the need for extensive training or additional software.
Excel offers flexibility in terms of data manipulation and customization. Users can build custom formulas, pivot tables, and charts to analyze their spend data in different ways. This allows for a tailored approach to spend analysis, accommodating specific business needs.
For small organizations or those with limited budgets, Excel provides a cost-effective solution for basic spend analysis. There's no need to invest in expensive spend management software, making it a practical option for companies with limited data and resources.
Excel allows users to create customized reports and visualizations, offering a degree of control over how data is presented. This can be beneficial for creating specific reports for stakeholders or executives.
One of the major limitations of Excel is its inability to handle large datasets effectively. Spend analysis often requires processing thousands or even millions of rows of data, and Excel struggles to scale with such volumes. As the data size grows, performance issues such as slow processing and potential crashes become more common.
Excel relies heavily on manual data entry, which increases the risk of human error. Even minor mistakes in formulas or data input can lead to inaccurate analysis and faulty decision-making. Manual processes also consume significant time and resources, reducing the efficiency of the spend analysis process.
Spend data in Excel is often prone to inconsistencies, such as variations in supplier names, regional formatting differences, and data classification issues. Handling these discrepancies manually can be time-consuming and may result in overgeneralized or incorrect categorizations, impacting the accuracy of the analysis.
Unlike dedicated spend analysis tools that offer automated data cleansing, classification, and reporting, Excel requires repetitive manual processes for updating and analyzing data. This lack of automation means that procurement teams spend more time on administrative tasks rather than gaining actionable insights.
Excel's reporting capabilities are limited compared to specialized spend analysis platforms. While Excel can create basic visualizations, it lacks advanced features like real-time data updates, interactive dashboards, and the ability to slice and dice data in multiple ways. This limits the depth of analysis and the ability to generate comprehensive insights.
Excel files are often shared through or cloud storage services, raising concerns about data security and version control. Additionally, collaboration can be challenging when multiple stakeholders are involved, leading to issues such as conflicting file versions and miscommunication.
Business Intelligence (BI) tools are a type of application software used to collect, structure, and visualize large amounts of data. While BI tools are commonly used across various business functions, they are particularly effective for spend data analysis. These tools help organizations gain deep insights into their spending patterns, aligning expenditures effectively with revenue, and driving smarter procurement decisions. Here&#;s a detailed look at the pros and cons of using BI tools for spend analysis, incorporating insights on Total Cost of Ownership (TCO), implementation challenges, and procurement-specific requirements:
BI tools excel at creating interactive dashboards and visualizations, making it easy for procurement teams to analyze complex spend data. These tools help users quickly identify trends, spot inefficiencies, and uncover cost-saving opportunities.
BI platforms process large datasets in real-time, enabling procurement professionals to work with the latest data. This allows for timely decision-making, which is crucial in responding to supplier performance or market shifts.
BI tools are scalable, accommodating the growing data needs of organizations of all sizes. They provide flexibility by allowing users to customize dashboards and reports based on specific procurement needs, which helps in tailoring analysis to different stakeholders.
BI tools can integrate with other enterprise systems, such as ERP and CRM platforms, to create a more comprehensive view of procurement data. This integration helps in pulling data from multiple sources for more holistic spend analysis.
While BI tools offer broad data analysis capabilities, they lack the procurement-specific functionalities found in dedicated spend analytics platforms. Dedicated spend analysis solutions come with pre-built features and procurement-specific metrics that BI tools do not natively support&#;.
BI tools can have a high total cost of ownership. This includes software licensing fees, customization costs, infrastructure investments, and ongoing support and training. For organizations with complex procurement needs, these costs can quickly add up. The TCO can be higher than expected, particularly if multiple tools are required to manage different aspects of spend analysis.
One of the major challenges with using BI tools for spend analysis is the longer time to value. Implementing and customizing BI tools to handle procurement-specific data often takes significant time and development resources. This delays the realization of cost savings and efficiency improvements, resulting in missed opportunities as organizations wait for full spend visibility and actionable insights.
While BI tools are flexible, they often require extensive customization to meet the unique needs of procurement teams. Configuring dashboards, creating procurement-specific reports, and structuring data for spend analysis can be time-consuming and resource-intensive. This complexity can delay the deployment of effective procurement analytics compared to pre-configured spend analysis solutions.
The handling of sensitive procurement data in BI tools, particularly cloud-based ones, can raise security and privacy concerns. Proper encryption, access controls, and compliance measures are necessary to protect against data breaches, adding to the overall cost and complexity of using BI tools.
BI tools provide significant flexibility, but this can also lead to variability in how data is interpreted. Different users may draw different conclusions from the same data, leading to inconsistencies in decision-making across the organization. Without standardized procurement data management processes, this flexibility can create challenges in maintaining alignment.
BI tools have limitations when applied to procurement-specific use-cases. The lack of procurement-specific features make BI tools less suitable for more complex procurement environments and larger enterprises. Specialized procurement analytics providers, like Sievo, are continually innovating and collaborating with the industry-leading procurement teams and third-party data providers to enhance their procurement analysis capabilities. BI tools typically do not have the same level of focus or investment in procurement R&D, which can limit their effectiveness for advanced spend analytics.
Spend analysis software is a specialized tool designed to help procurement teams gain a deep understanding of their organization's spending patterns. By consolidating data from various sources, such as ERP systems, Purchase-to-Pay suites, and 3rd party datasets, spend analysis platforms provide procurement teams with actionable insights that go beyond what can be achieved with Excel or general Business Intelligence (BI) tools.
Sievo Spend Analytics ranked as a top business value enabler by SpendMatters!
Spend analysis software is particularly beneficial for large enterprises with complex procurement needs, offering advanced analytics, safe integrations, faster time to value, user training, and procurement-specific R&D and innovation capabilities. However, for smaller organizations, the higher costs and complexity may be less practical, and lighter solutions like Excel or BI tools might be a better fit until their procurement needs grow to a larger scale. Next, we outline the pros and cons of spend analytics software:
Like BI tools, spend analysis software excels in data visualization, providing procurement teams with holistic view and interactive dashboards. However, spend analysis platforms take this further by offering procurement-specific features, dashboards, insights, and AI assistance, making it easier for users to identify trends and opportunities.
Similar to BI tools, spend analysis software offers real-time data processing, ensuring that procurement teams have access to the most up-to-date information. However, the advantage of dedicated spend analysis software lies in its ability to automatically cleanse and classify procurement data, reducing the time and effort needed to prepare data for analysis, and enabling faster, more accurate insights.
Spend analysis software providers, such as Sievo, invest heavily in procurement-specific research and development. This R&D focus ensures that these platforms stay at the cutting edge of procurement analytics, offering features that address the unique challenges of procurement, such as supplier risk management and Scope 3. In contrast, BI tools and Excel lack this level of specialization, making spend analysis software the better choice for procurement organizations that want to outperform their peers.
Unlike Excel and BI tools, spend analysis software comes with built-in procurement-specific use-cases and actionable recommendations. These platforms are designed to handle complex procurement data, automate categorization, and provide AI-driven insights. For example, spend analysis software can automatically identify cost-saving opportunities, monitor contract compliance, and consolidate contracted spend, all of which are critical for large enterprises managing complex procurement operations.
Spend analysis software offers greater scalability than Excel and more flexibility than generic BI tools. These platforms are designed to handle the complexities of large-scale procurement environments, processing massive amounts of spend data from multiple sources without performance decrease. Spend analysis software provides advanced module options tailored to procurement needs and use-cases, such as CO2 Analytics, that go beyond the capabilities of BI tools.
Spend analysis software typically offers faster time to value compared to Excel and BI tools, as it comes pre-configured with procurement-specific features. This means less time spent on customization and more immediate access to actionable insights. For large enterprises, this faster time to value translates to quicker realization of cost savings and improved procurement performance.
Leading spend analytics providers have wide communities of global users and they offer training and learning resources for their customers. This collaboration often extends to joint product development, where clients can influence the roadmap of the software enhancements based on their needs and challenges. This level of community learning and collaboration ensures that the software evolves in line with the needs of large enterprises, offering cutting-edge features that go beyond the capabilities of general-purpose tools like Excel and BI platforms.
While BI tools offer robust data security measures, spend analysis software is specifically designed to handle sensitive data and ensure compliance with regulations. These platforms offer advanced security features, such as data encryption, role-based access control, and audit trails, which are essential for large enterprises managing global procurement operations.
The advanced features and capabilities of spend analysis software come at a premium, making these platforms less accessible for organizations with more limited budget. The cost associated with implementing these platforms can be too high for SMEs, which may not have the volume of data or budget to justify the investment. In these cases, lighter-weight solutions like Excel or BI tools may be more appropriate. For large organizations, the investment in spend analysis software quickly pays off in efficiencies and realized savings, however.
While spend analysis software offers extensive features tailored to procurement, customization may be limited compared to the full flexibility of Excel or BI tools. However, leading provider Sievo addresses this limitation by offering tools like Craftboards and self-service dashboards, which empower users to create the specific views and reports they need for their business cases. These features provide a level of customization while maintaining the structure and stability of a dedicated platform.
Spend analysis software offers significant advantages over Excel and BI tools, particularly for large enterprises with more complex needs. With features like procurement-specific analytics, faster time to value, and dedicated R&D, these platforms enable organizations to optimize their strategies and drive 360 cost savings.
Leading providers like Sievo stand out in the market with extensive industry experience, year-after-year industry recognition, and commitment to joint-innovation with top enterprise clients. However, for smaller organizations, advanced features and depth of insights may not be mandatory elements, and lighter solutions like Excel or BI tools might be a better fit until their procurement needs and ambition level grow to a larger scale.
If you&#;re considering spend analysis solutions, these key questions will help you understand the differences between dedicated tools and more general BI or Excel setups. Use this Q&A to explore which option best suits your procurement needs.
Dedicated spend analysis tools like Sievo&#;s offer automated data extraction, cleansing, and classification across multiple ERPs. This eliminates the need for manual data crunching, which is common in Excel or BI tools. Unlike general BI tools, which focus on reporting, spend analysis tools are purpose-built to deliver procurement-specific insights, including supplier performance, cost-saving opportunities, and category-level analytics.
Spend analysis software automatically consolidates and enriches data from internal and external sources, reducing human errors that commonly occur during manual processes in Excel or Access. The tools provide real-time updates and allow users to correct or approve data directly in the interface, improving data accuracy and auditability&#;.
Yes, tools like Sievo&#;s spend analysis software are designed to integrate seamlessly with various ERPs and other data systems. They can handle data from multiple sources, consolidating it into one platform without disrupting existing workflows. This is a major advantage over Excel.
Spend analysis software significantly enhances procurement visibility by providing a comprehensive, centralised view of an organisation's spending patterns. Spend analysis tools provide a holistic view of procurement data by integrating various metrics such as spend by supplier, category, delivery performance, CO2 emissions, and compliance. This allows procurement teams to contribute beyond financial metrics and gain insights into areas like carbon, risk and diversity.
Excel is prone to human error, slow updates, and limited scalability. It also requires significant manual effort for tasks like data cleansing and consolidation. In contrast, spend analysis tools automate these processes, provide real-time visibility, and offer advanced analytics like supplier risk assessments and predictive insights&#;.
Dedicated spend analysis tools offer procurement-specific analytics that go beyond what BI tools can offer. These include category management insights, supplier performance tracking, predictive insights, and sustainability metrics like carbon emissions. BI tools focus on broad data analysis and visualisation, while spend analysis tools are tailored to procurement's needs&#; and use cases.
Spend analysis platforms like Sievo&#;s can track and report on Scope 3 emissions, which make up the largest share of a company's carbon footprint. These tools combine internal and third-party data to provide actionable insights into emission reduction opportunities, helping companies align procurement decisions with sustainability goals&#;. Without spend, supplier and category level information, emission reduction plans are harder to execute.
Spend analysis tools like Sievo are designed for ease of use, even for non-technical users. Features like automated data classification, self-service analytics, and intuitive dashboards enable users to quickly access and interpret data without needing deep technical expertise. This ease of use encourages higher adoption rates compared to Excel and BI tools.&#;
User adoption rate is critical in spend analytics because the value depends on how effectively the insights and opportunities are used across the organisation. High adoption ensures that the data insights are widely accessed, leading to better procurement decisions and stronger cost-saving strategies. When more users actively engage with the tool, also data accuracy and classification improves through collaborative corrections and feedback.
About Sievo
We are the procurement analytics solution for data-driven enterprises.
We give procurement, finance, and leadership teams a single source of truth and radical transparency in all sourcing decisions. Our solution helps you choose the right suppliers, deliver savings and manage compliance with confidence. Not only that, we enable a sustainable, diverse, and resilient supply base.
We master the art of extracting, classifying, and enriching data across all ERPs, procurement systems, and external data sources, saving your valuable time.
Simply put, we&#;re pretty damn good at turning even the crappiest data into actionable insights!
We&#;ve pushed the boundaries of spend analytics for two decades &#; and we&#;re just getting started. We bridge the data-to-action gap and power agile procurement by combining AI with procurement expertise.
Procurement organizations need an analytics partner they can trust. We&#;re large enough to deliver, small enough to care
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