Spend outcome tool

UK, remember your settings and improve government services. We also use cookies set by other sites to help us deliver content from their services. You can change your cookie settings at any time. An overview of spend and outcomes in local authorities for public health teams and commissioners. SPOT for local authorities was redeveloped from an Excel-based tool to a web-based tool in These are incomparable with the current tool due to changes in methodology and data.

You can use the current version of SPOT to look at historic local authority data. If you wish to obtain a copy of one of the previous Excel tools email healtheconomics phe. This tool is no longer being updated due to the lack of available CCG spend data. Using the SPOT , public health teams and commissioners can:. Removed previous versions of SPOT for local authorities which have been replaced by the web-app version released in It also includes standardizing the spend data for easy viewing.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. Data is often missing specific fields, and misspellings and abbreviations are common — as are incorrectly coded fields. Classification typically involves grouping several suppliers of the same parent company or organization.

For example, Microsoft purchases like Microsoft , Azure, and Surface should all be grouped together. At the same time, you can also categorize the data into meaningful groups like marketing, office supplies, software to identify how and where the business is spending its money. 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 to the global spending to make better sourcing decisions.

The last step is to identify opportunities for savings and other procurement improvements. Analysis can be geared towards investigating all sorts of business problems, such as ensuring that you have negotiated the best contract deals per supplier, or confirming buyers are purchasing from preferred suppliers.

With this, you can identify opportunities of reducing the number of suppliers per category and negotiating better rates. The best probable method for cost savings can only be realized after the confirmed estimates have been calculated properly. There are countless opportunities and insights to discover in your spend data.

This chapter will cover six of the most fundamental procurement analytics exercises you can use. Tail spend is easy to ignore, but at a big cost. It is the place where procurement organizations may be leaving money on the table and utilizing their resources inefficiently. With companies making millions of purchases every year, purchases that are too small or too infrequent can go overlooked. Procurement teams invest heavily in their core spend areas, but the tail-end remains a largely untapped opportunity for most companies.

There is little understanding of how much money is involved in tail spend, and even less knowledge of how to manage it. This can lead to potentially losing millions of dollars annually. Doing an in-depth spend analysis on tail spend helps encourage compliance and identify maverick spend, which refers to non-compliant transactions. The most common way of doing this is carrying out a simple spend analysis, and then ranking the suppliers based on annual spend.

Here, the Y-Axis represents spend per supplier "Total Spend by Supplier" and the X-Axis represents the total supplier base "Supplier" , with suppliers ranked in descending order of size from left to right. So, to the furthest left will be the suppliers where you buy the most goods and services from. On the farthest right will be the suppliers where you spend the least. Everything else is "tail spend". Tail-end spend management has been growing recognition and increasing importance within procurement.

Putting a significant effort on it may not only yield potential savings, but also reduce costs and get more spend under management. When there is enough visibility into the tail spend, it is easier to identify areas that need to be sourced strategically.

Organization that are successfully managing tail spend often start by segmenting the tail spend away from strategic sourcing managers, and allocating dedicated resources with the right incentives, tools, and capabilities to manage the tail.

Supplier spend analysis is the task of identifying the amount of spend coming from critical vendors. It involves creating a detailed spend profile for each vendor using historical consumption data.

Knowing this can help focus efforts on getting the best value from these preferred vendors and consolidating the relationships.

Different types of vendor reports visualize spend insights in several ways: by vendor, by category, and by geography, for instance. Vendor reports enable year on year comparison and analysis for data driven decisions.

Spend can be optimized by identifying and implementing opportunities for consolidation. There are usually many low-value transactions with multiple vendors across many business units. The total number of one-off and small value vendors is usually big. Knowing this can help in streamlining and leveraging spend by identifying contract leakages and maverick spending. The aim is to reduce the number of vendors in each category.

Every dollar spent is important and savings opportunities can be missed through off-contract purchases. Vendor spend analysis will facilitate the identification of purchasing trends, buying patterns, as well as monitoring utilization and spend consolidation of key strategic 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 in delivering savings and to realize which projects bring strategic importance to the organization.

With this, you can easily figure out which action to take based on what gives the most impact on staff or operations, and what the risks associated are. Access to detailed information on spend by category gives you the data to determine priorities and allocate resources to deliver the highest return on investment for the level of effort required. It takes into account every individual purchase, 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. Doing this analysis can highlight the different opportunities for purchasing in the business and potentially 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. Suppliers may reward early payment of invoices with discounts, but early payment of invoices may also mean lost interest on working capital. Payment term spend analysis utilizes data and gives a comprehensive view that enables you to identify unrealized discounts through late payments of invoices or opportunities to negotiate better payment terms to capture unrealized interest.

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 spend with vendors by contract to identify spend leakage through non-compliant contracts. It ensures that the best contract deals per supplier have been negotiated and that all the buyers are purchasing from preferred suppliers. A dashboard in the software context is referred to as a user interface or view that captures and presents a holistic view of information about a series of predefined topics.

A spend analytics dashboard is a dashboard that visualizes sets of spend data into charts for the purpose of analysis. These sets of data are selected based on predefined parameters, business targets, or KPIs. The benefit of a dashboard is an instant high-level picture of spend data. Spend analytics dashboards are also referred to as charts or reports in some contexts. In this chapter, we will cover 9 basic types of spend analysis dashboards used in Sievo.

If you'd like to see a broad overview of all that Sievo can offer, check out this two minute demo video to see it in action. 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 above, this view is filtered by year-to-date and presents the data by three key aspects: category, organization, and supplier.

It shows multiple charts that visualize different sets of spend data. You can see in this example the distribution of spend by categories raw materials, indirect, packaging, and undefined , distribution by organization Americas and EMEA as well as the distribution of spend by top 10 suppliers. 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. You simply select Americas in the organization chart and the view automatically filters the data by Americas.

Now you see a more defined view of the dashboard covering charts that visualize spend data that was classified to the specific organization level. Below, you can see an example of the same Spend Performance Dashboard filtered by the Americas region with one click. A Supplier Performance Dashboard visualizes all relevant data of a specified supplier, giving you the degree perspective. In this example, you can see relevant analytics on the top supplier by spend ranking.

This provides transparency to what you are purchasing from a specific supplier as well as the relevant payment terms across business units. By having overview on supplier spend data, you are also able to compare a supplier against its peers, gaining insights on performance opportunities. A Supplier Performance Dashboard is useful in, for example, strategizing supplier meetings to re-negotiating payment terms or ensuring compliance for better payment terms across all your business units.

The Category Performance Dashboard is similar to the Supplier Performance Dashboard, but instead of a specified supplier it shows all relevant data of a selected category. With the Category Performance Dashboard, you can analyze the spend distribution throughout your categories, keep track of purchase order development, material price development, and see which suppliers your business units are sourcing from.

The Category Performance Dashboard is especially useful in providing category management insights. You can identify price opportunities or find materials sourced from a single supplier which may result in a business risk such as a single point of failure. On top of that, you can track how much was purchased with or without a PO and assess purchase price development by drilling down to the lowest category level. A Supplier Base Performance Dashboard gives you the ability to analyze data from the whole supplier base.

You can keep track of your top suppliers and identify tail-spend suppliers, giving you transparency on consolidation opportunities and helping you tackle the tail spend to mitigate risks or create savings. The Supplier Base Performance Dashboard is great for when you want to do a tail spend analysis but can also be used for internal benchmarking purposes. You do this by looking at how fragmented or consolidated your supplier base is in different business units in a single category. With a Sourcing Performance Dashboard you can immediately see from which regions your business units are sourcing.

You can also gain transparency into which materials are sourced internationally vs domestically and evaluate potential regional risks. All this helps you assess and anticipate the impact of trade or geopolitical turmoil. A Sourcing Performance Dashboard is useful in managing regional risks as well as identifying where certain goods or services are coming from.

You can for example identify savings in logistics costs from imported goods by switching to suppliers that are geographically closer. This refers to the costs involved in processing transactions. When filtering by a specific category, discrepancies between business units or suppliers can be identified and assessed for strategic process optimization. These performance insights help you identify opportunities in streamlining your purchase process. A Price Performance Dashboard helps you analyze price discrepancies between different suppliers.

When filtering by a specified region, category, and supplier, you can determine price opportunities. A Price Performance Dashboard allows you to identify such price opportunities globally as well as regionally, helping you to discover the price range of your specified category.

The price opportunities presented in a Price Performance Dashboard are useful when you are negotiating for cheaper prices or want to find the cheapest suppliers in a category. A Currency Performance Dashboard gives a proper overview of spend distribution in different currencies and helps you recognize which categories or suppliers are purchased using different currencies. You gain transparency on risks associated with different currency purchases such as foreign exchange risks.

A Currency Performance Dashboard is useful when you filter by a specified category or supplier, as this helps you to determine materials or suppliers that could get more expensive when the purchasing currency would strengthen in relation to the local currency. This chapter has reviewed just some of the basic spend analytics dashboards. The ready-made charts in the above-mentioned 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 Dashboard allows you to build reports to meet your specific needs. These best practices in spend analysis come from our close to 2 decades of experience helping enterprise companies transform their spend data into actionable insights.

Categorizing at the item level proves to be the most effective way to do spend analysis. This not only provides visibility but also enables more details of all the attributes, enough to do estimates and comparisons.

Higher-level classification has its own benefits, but item-level proves to be more effective as it gives a precise view of spending with each supplier and for each commodity. Organizations should adopt a common internal taxonomy or industry-standard classification schema.

This standardization is key to driving accurate organization and correlation of spend data and to enabling actionable analyses.

Often broader than internally developed classification codes, these standards allow organizations the ability to map all spend data to a single schema.

Pursue a permanent solution versus one-time efforts. Using traditional, labor-intensive procedures and systems are not recommended due to the volume and complexity of spend data within an organization. External services usually provide a temporary solution, which requires the organizations to engage with the consultants on a continuous basis to keep data up-to-date. Outsourcing also limits the transfer of the process knowledge and expertise to the organization, leading to dependence upon consultants in the future.

Adopting a more sustainable and standard procedure can help organizations get monthly refreshes of their spend data, and a more efficient operation of examining the spend categories. Have an automated approach to cleansing and classification. Automated spend analytics solutions capture data classification rules and attributes for a wide range of spend categories.

Because of their self-learning abilities, these solutions can present what the sourcing experts know into the system. But there will be a need for commodity managers to classify exceptions from time to time. Establishing automated extraction routines to aggregate and refresh data on a regular basis allows accurate and repeatable spend analyses.

Automation also increases the frequency of analysis, which is critical as the business environment is dynamic, with prices changing and contracts expiring all the time. Access all spend-data sources within and outside the organization. There are times when your vendors, suppliers, or other affiliates have better data than you. Organizations that access spend data from all relevant sources can gather a more comprehensive and accurate idea of their total spending.

Continuously improve and expand the scope of spend data management program. Spend data management is an ever-changing process. Organizations should constantly look for ways to expand the uses and scope of spend, and their data cleansing and classification capabilities. Conducting reviews will help identify immediate areas for improvement and illustrate the positive impact that a particular initiative has on the performance of the organization.

Collaborate with IT and other key stakeholders, like finance, in the whole process. To achieve full potential savings, a collaborative partnership between procurement and other business units must be created, and everyone should be held accountable for results. Leveraging spend data requires cooperation within the entire procurement organization. This in turn creates a positive feedback loop for improving performance.

Define category strategies and measure impact. Develop category plans aligned to the business objectives and key stakeholders with a strategic approach to maximize value, reduce risk, and effectively manage the supply of goods and services.

These plans should influence sourcing strategies and initiatives. A careful review of these strategies will assess and confirm their business impact and determine if a revision or repetition is required. The data provided by the procurement teams can prove valuable as it generates insights about what the organization buys and how it makes purchases.

These insights and ideas must be implemented into actual strategies that will drive savings to the bottom line. Act on these strategies and make sure that they will be translated into savings opportunities.

Many organizations tackle the problem of spend visibility, but these projects often fail in delivering the value that was expected initially, despite the significant need that the organization had for effective spend analytics.

Here are some reasons why spend analysis projects fail. The most common reason why most spend analysis projects fail is because of the poor quality of data. There are times that suppliers have better data than the systems the organizations can provide. Common examples of dirty and inconsistent data include basic hygiene issues like empty data fields and wrong spellings which can interfere with analysis. An effective spend data classification and analysis requires detailed information but often has unstructured data within different business systems.

The information is often rife with errors and discrepancy in different departments or missing critical data fields, such as supplier name, product attributes, or account codes. For most large organizations, classifying their billions of dollars of spend is not easy. The problem is not just in volume of spend, but the immense sets of spend related data, which could take years to properly classify. Human work hours alone are not sustainable, as it would be impossible to keep up with constantly incoming data while repeating the same long processes.

Other methods like classifying spend data only at the highest-level commodity class provide insufficient insights and often give inaccurate analysis. The key thing is to build in appropriate checks and balances so most errors can be caught and corrected immediately.

Making sure that this is done consistently will maintain trust in the data and in the classification process and enable the data to be used consistently for ongoing decisions.

The leadership team also has a role to play in why some spend analytics projects fail. Failure may be due to a lack of agility and continuous involvement or sponsorship by executives in the analytics process.

Many business leaders trust the familiar way of doing things and may resist adopting a more data-driven approach. The top management may not be the people who literally put spend analysis insights into strategic practice. The solution is to adopt a more lightweight approach. Letting them know of project progress will ensure they see immediate, accumulative results. Getting them in the loop drives better engagement and management buy-in.

Part of the reason that many spend analytics projects fail is that organizations rush to accumulate and analyze as much data as possible all at once and without much of a plan. This usually leads to huge costs and an overwhelmed team. Beginning the spend analysis process with a new robust software can feel like there are more opportunities than there are resources to exploit them. Start small. Hide this message. Home Health and social care Public health Sexual and reproductive health.

The information provides an overview of spend and outcomes across key areas of business for LAs, including: the potential breadth of issues hindering comparisons between outcomes and spend how to identify if the spend or outcomes data, or both, for their LA is suitable for drawing comparisons from next steps for interpretation where data comparisons can be made how to prevent misinterpretation.

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