Everything You Need to Know About Modern Spend Analytics

What is spend analytics?

Spend analytics leverages the power of data analysis to transform raw expenditure data into actionable insights.

Spend analytics is the extensive use of sophisticated data analytics methods on spending information. By utilizing technologies like artificial intelligence (AI), machine learning, and predictive modeling, spend analytics can offer even greater insights.

This helps businesses evaluate supplier risks, forecast future spending trends, and gain deeper insights that can inform strategic procurement choices in addition to comprehending past spending patterns.

The importance of spend analytics in business.

Every dollar matters in today’s intensely competitive corporate environment. Spend optimization is fast becoming a strategic requirement rather than merely a good practice. This is where spend analytics really shines, giving companies the ability to turn raw spending data into valuable insights.

Spend analysis is one of the most important steps in enhancing the sourcing of goods, services, and materials. It’s frequently seen as an essential component of a larger spend management process that also includes automated approval workflows, vendor onboarding and payments, and accounting entries.

Spend analysis helps reduce the cost of acquiring products and services by obtaining information about the company’s suppliers and payment terms.

It assists businesses in monitoring important spending indicators and offers a starting point for evaluating the results of fresh approaches and cost-cutting initiatives. Through the process of comparing spending metrics to industry norms, businesses can identify opportunities to reduce expenses and increase profitability.

Key components of spend analytics.

The power of spend analytics depends on a well-maintained system with multiple essential components. Here, we examine the fundamental components of a strong spend analytics process.

Data collection.

The foundation of spend analytics is the careful collection of precise and comprehensive data. If a separate spend analytics tool is used, this data will need to come from many sources within your company. If you plan on relying on your ERP software to produce spend analytic reporting, you’ll most likely need to wait until after the close to collect the data you need.

Data to be collected includes:

• Purchase orders: Granular details regarding procured goods or services, including vendors and pricing.
• Invoices: Comprehensive information on received items, facilitating reconciliation with purchase orders.
• Accounts payable (AP) data: Information pertaining to payments made to suppliers.
• Approvals for each purchase order: Approvals may be needed from several areas of your organization, including legal for contract terms, IT for SOC, and budget owners.
• Inventory data: Detailed records on stock levels and historical usage patterns.
• Contract data: Defined terms and conditions negotiated with vendors.
• Reimbursable expenses: Such as travel and entertainment.
• Cycle times: Time to approval, aging AP, and time spent on bills is data that can help identify bottlenecks and inefficiencies in the spending process.

Effective data collection requires:

• Identification of all relevant data sources: Unless a comprehensive spend management system is used, collaboration across departments like procurement, finance, and operations is crucial to identify all pertinent data streams.
• Standardization of data collection processes: Ensuring consistent data formats and collection methods across all sources minimizes errors and facilitates analysis.
• Automation of data collection whenever possible: Utilizing electronic invoicing and data integration tools streamlines the process and reduces manual data entry errors.

Data cleansing.

Raw data aggregated from multiple sources can be riddled with inconsistencies, errors, and missing information. This is where data cleansing steps in. It’s the critical process of verifying, correcting, and standardizing your data to guarantee its accuracy and reliability for analysis.

Data-cleansing activities encompass:

• Identification and correction of data errors: This process involves meticulously checking for typos, duplicate entries, and missing values.
• Standardization of data formats: Ensuring consistency in units of measurement, currency, and date formats across the entire dataset.
• Data enrichment: Supplementing existing data with additional insights from external sources, such as market rates or supplier performance data.

In well-designed P2P platforms, accounting automation and approval workflows ensure transaction data is clean before it is booked.

Data categorization.

Once your data is cleansed, it’s time to organize it into meaningful categories that facilitate analysis. This process, called data categorization, involves grouping similar items based on predefined criteria.

Common categorization methods in spend analytics include:

• Spend category: Grouping purchases by product or service type (e.g., office supplies, IT equipment, transportation).
• Supplier category: Classifying suppliers based on industry, size, or location.
• Location: Categorizing spending by department, branch, or geographic location.

This is another step that can be taken over by automation. In a platform like Airbase, machine learning and AI can code transactions correctly based on past behavior.

Data analysis.

Having meticulously compiled, cleansed, and categorized the data, the next component is data analysis, where a diverse array of techniques are employed to extract actionable insights from spend data.

Common data analysis techniques in spend analytics include:

• Spend cube analysis: This multi-dimensional analysis allows you to view spending data from various perspectives (e.g., category, supplier, location). It is used to help improve strategic sourcing.
• Trend analysis: Identifying patterns in spending over time, such as seasonal fluctuations or changes in supplier pricing. This can be useful for cash-flow management and budgeting.
• Benchmarking: Comparing your spending patterns with industry averages or competitor data to identify areas for improvement.
• Variance analysis: Investigating discrepancies between budgeted and actual spending to identify cost overruns or areas for optimization.

Reporting and visualization.

The insights derived from data analysis are powerful, but their effectiveness hinges on clear communication. Reporting and visualization are crucial steps in ensuring your findings are easily understood and actionable.

Effective reporting and visualization in spend analytics involve:

• Creating clear, concise reports: Reports should present key findings visually, with concise summaries and actionable recommendations.
• Utilizing data visualization tools: Charts, graphs, and dashboards help communicate complex data in a readily understandable format.
• Tailoring reports to specific audiences: Reports should be designed with the needs and decision-making level of the intended audience in mind.

Benefits of spend analytics.

Spend analytics is becoming more than just a tool for decreasing costs; it’s becoming a strategic necessity for modern businesses. Through the utilization of data, spend analytics enables organizations to access cost-savings opportunities and reduce risk.

Driving cost reduction.

One of the most well-known benefits of spend analytics is its ability to identify and eliminate hidden opportunities for cost savings.

Spend analytics facilitates continuous improvement by allowing businesses to benchmark their spending data against industry averages. This data-driven approach helps identify areas where your organization might be incurring higher costs compared to competitors.

It can also lead to improved inventory management. By providing insights into historical spending patterns and forecasting future demand, businesses can optimize inventory levels. This reduces storage costs, minimizes the risk of stockouts, and leads to improved overall cash-flow management.

Improved supplier management.

Spend analytics is more than just finding ways to save money; it also fosters closer interactions with suppliers. Spend analytics gives procurement and finance teams important information about supplier performance parameters, such as quality, delivery timeframes, and pricing, so they may choose and negotiate with the best vendors.

By fostering transparency and open communication, spend analytics helps build stronger relationships with key vendors, leading to improved collaboration and mutual benefit. This proactive approach enables businesses to mitigate risks associated with unreliable suppliers.

Enhanced contract compliance.

Spend analytics plays a crucial role in ensuring contract compliance, which is essential for safeguarding your bottom line. It simplifies the process of monitoring adherence to established terms and conditions.

It can also identify potential discrepancies between contracted terms and actual spending patterns early on. This allows for timely intervention and corrective action, preventing financial losses and legal ramifications associated with non-compliance.

Better decision-making.

Spend analytics empowers businesses to move beyond reactive cost cutting toward proactive strategic sourcing. Analyzing historical spending data and market trends allows for the identification of new vendors, improved lead times, and a more resilient supply chain that can adapt to market fluctuations.

Data-driven insights from spend analytics also help businesses develop more accurate and budgets for future procurement activities. This ensures efficient resource allocation and minimizes the risk of budget overruns.

Finally, spend analytics enables more focused analysis within specific categories, leading to improved category management strategies and long-term cost optimization.

The spend analytics process.

Extracting actionable insights from vast amounts of spending data is where spend analytics emerges as a transformative tool. This intelligence empowers organizations to make data-driven decisions that give better visibility and insight into their spend.

Here’s a breakdown of the crucial stages.

1. Initial data assessment.

The critical first step involves evaluating the quality, completeness, and consistency of your data. Techniques like data profiling and data cleansing ensure you’re working with reliable information for analysis.

• Importance: A robust spend analytics process hinges on the quality of the underlying data. Inaccurate or inconsistent data can lead to misleading insights and hinder the effectiveness of cost-saving initiatives.
• Methods: Data profiling involves summarizing key attributes of your data to identify inconsistencies or missing values. Data cleansing involves correcting these errors and inconsistencies to ensure data integrity. Common data cleansing techniques include deduplication (removing duplicate entries), correcting data formats, and imputing missing values.

2. Spend data mapping.

Mapping involves organizing and categorizing your data into a standardized format. This might involve grouping purchases by category (e.g., office supplies, IT equipment), supplier, or location. Effective data mapping facilitates easier analysis and identification of patterns.

Techniques for effective mapping.

Data mapping is the process of organizing your data into a standardized format that facilitates analysis. Common techniques include:

• Standardized categories: Grouping purchases by predefined categories like product/service type, supplier, or location.
• Dimension mapping: Defining the different perspectives (dimensions) you want to analyze your data from, such as time period, department, or business unit.
• Data hierarchy creation: Establishing a hierarchy within your data categories for a more granular analysis (e.g., department within a branch within a region).

3. Pattern and trend identification.

Advanced analytics techniques like spend cube analysis and trend analysis are used to identify patterns and trends in your spending habits. This could reveal areas of overspending, inefficient supplier utilization, or seasonal fluctuations in demand.

How to analyze spending patterns and trends.

Once your data is cleansed and mapped, it’s time to leverage advanced analytics techniques to uncover hidden insights.

Spend cube analysis allows you to view your spending data from multiple perspectives simultaneously (e.g., category, supplier, location).

Trend analysis helps identify patterns over time, such as seasonal fluctuations in demand or changes in supplier pricing. By analyzing these trends, you can anticipate future spending patterns and make informed procurement decisions.

4. Opportunity analysis.

After identifying patterns and trends, the focus shifts to uncovering potential savings opportunities. This involves analyzing identified areas of inefficiency and exploring solutions like supplier consolidation, negotiation of better terms, or process optimization.

Identifying and capitalizing on savings opportunities.

Opportunity analysis involves leveraging the insights gleaned from pattern and trend identification to pinpoint areas where cost savings can be realized.

This might involve identifying opportunities for:

• Supplier consolidation: By consolidating purchases from multiple vendors into a smaller group of high-volume suppliers, businesses can leverage economies of scale and negotiate more favorable pricing.
• Improved negotiation strategies: Spend analytics provides valuable insights into historical spending patterns and industry benchmarks, empowering procurement teams to negotiate more effectively with existing vendors.
• Process optimization: By identifying inefficiencies in procurement processes, such as slow approval times or slow invoice processing times, businesses can streamline workflows and reduce administrative costs.

With Airbase, businesses can identify cost-saving opportunities, eliminate wasted spend, and make data-backed decisions about future spending.

5. Implementation and monitoring.

The final step is transforming your insights into action. This involves developing a plan to implement identified cost-saving opportunities and monitor progress over time. Tracking key metrics helps assess the effectiveness of your strategies and identify areas for further improvement.

Strategies for implementation and monitoring.

After identifying potential savings opportunities, it’s crucial to develop a clear action plan for implementation.

This plan should outline specific actions, timelines, and responsibilities for each initiative.

Additionally, key performance indicators (KPIs) should be established to monitor progress and measure the effectiveness of implemented strategies. Common KPIs used in spend analytics include:

• Cost savings achieved.
• Reduction in supplier base.
• Improvement in contract compliance.
• Procurement cycle time reduction.
• Spend under management.

Challenges in implementing spend analytics.

Despite the numerous benefits of spend analytics, implementing a successful program can present a set of challenges. Here, we delve into some of organizations’ most common obstacles and explore strategies to overcome them.

Overcoming common obstacles.

While the potential rewards of spend analytics are significant, the road to implementation is not without its hurdles. Here’s a breakdown of the typical challenges faced by organizations and strategies to overcome them.

Best practices for effective spend analytics.

These spend analytics best practices are derived from our expertise in assisting underserved mid-market and larger organizations in converting their expenditure data into useful insights.

1. Ensure data accuracy.

The foundation of any successful spend analytics program lies in data integrity.

Methods for guaranteed accuracy: Implement rigorous data quality checks throughout the process. Utilize data cleansing techniques to identify and rectify inconsistencies, errors, and missing values. Standardize data formats across all sources to ensure seamless integration and analysis. Regularly monitor data quality metrics to maintain data integrity over time.

2. Conduct regular and consistent analysis.

Consistent analysis is key to uncovering valuable insights.

Importance of regularity: Schedule regular data analysis sessions to identify spending trends, track progress towards goals, and identify new opportunities for optimization. This could involve weekly, monthly, or quarterly reviews depending on the volume and complexity of your data.

Maintaining consistency: Develop a standardized approach to data analysis. This ensures consistency in how data is categorized, analyzed, and reported, allowing for easier comparison and trend identification over time.

3. Encourage cross-department collaboration.

Break down silos and foster collaboration between procurement and other departments.

Benefits: Collaboration with departments like finance, operations, and logistics provides valuable insights into spending patterns and facilitates a more holistic approach to procurement optimization.

Strategies for collaboration: Establish cross-functional teams dedicated to spend analytics initiatives. Regularly share insights and findings with key stakeholders across departments. Encourage open communication and collaboration to leverage the expertise of various teams.

4. Leverage advanced analytics techniques.

Don’t settle for basic insights! Advanced analytics can unlock hidden potential.

Benefits of advanced techniques: Techniques like spend cube analysis, variance analysis, and machine learning can uncover deeper patterns, identify anomalies, and predict future spending trends. This allows for more informed decision-making and proactive cost-saving strategies.

How to utilize them: Invest in spend analytics solutions that offer advanced analytics capabilities. Provide training to procurement teams on how to interpret and utilize the insights derived from these advanced techniques.

Summarizing the power of spend analytics.

Spend analytics can be used to supplement existing end-to-end and point solutions as the data-integration layer. A 2022 Spendlightenment Survey of Finance Professionals revealed that there was an increase in demand for tools to gain visibility and control over company spend. 65% believed that their current lack of control over spend will negatively impact their growth, over 90% wished for more visibility, control, and automation around how their company spends money, and 39% said they are controlling less than 50% of their risks.

However, as more organizations realize the potential of comprehensive spend management systems to drive spend visibility and savings, spend analytics can serve as the foundation for a digital transformation of the whole procurement function.

“In an era where data-driven insights are crucial, Airbase offers a competitive edge by enabling real-time visibility and strategic planning,” said Patrick Reymann, Research Director, IDC. “This platform helps businesses navigate procurement complexities with ease and precision.”

Airbase spend analytics feature lets you monitor requests as they move through the process, see spend by vendor, department, and category, track pre-approved vs maverick spend, identify cost saving opportunities, eliminate wasted spend, and make data-backed decisions on future spend.

There are even more benefits when companies leverage Airbase as the single source of spend insights:

• Provide real-time visibility to your leadership.
• Businesses can get strategic questions answered with the ‘Summary’ tab
• Finance teams can manage spending more proactively by using analytics and reporting, as opposed to reacting to expenditures after the fact by creating customized spend reports with the “Analyze” tab Effective workflows are ensured by seamless departmental and vendor collaboration, which also fosters the culture of openness and trust that is necessary for long-term vendor collaborations.
• By automating repetitive processes, procurement teams can devote more of their time to figuring out how to use procurement to create greater strategic value.
• Promote compliance and cultivate robust vendor relationships by streamlining vendor onboarding, automating invoice processing, and enhance risk management with the ‘Productivity’ tab

“I was planning to build these reports and workflows separately. Glad to know I won’t have to now and can view it directly on Airbase” — Harness

See how Airbase helps companies leverage spend analytics — book a demo with us!