Page Comparison

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Understanding the chart

The Comparison Waterfall Chart is a visual representation that allows the display of two sets of data, namely KPI Data and Company Data, side by side. The data presented in this chart is represented as percentages. In this chart, the value of the first price point, known as "Global_List_Price," serves as the basis for comparison, representing 100%. All other data points are calculated and displayed relative to this baseline.

The chart provides support for two distinct modes: Aggregated mode and Drill down mode. In Aggregated mode, the price points are grouped together based on predefined categories. This grouping enables a higher-level overview, allowing users to quickly compare and analyze data within these categories. On the other hand, the Drill down mode provides a more detailed perspective. It enables users to explore all the individual price points included within the categories. In this mode, all the price points and adjustments are displayed and calculated, providing a comprehensive view of the data. From high-level analysis to granular examination of individual price points and adjustments, the Comparison Waterfall Chart is a powerful tool to help you identify areas of improvement to be more competitive against industry peers.

The comparison waterfall enables benchmarking against other companies in order to identify best practices in terms of pricing structure and to identify profit leakage so as to derive levers of improvements.

This is calculated with revenue.

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Understanding the chart

The bar chart presents Key Performance Indicator (KPI) Data, showcasing three separate bars on the X-axis representing the bottom quartile, median, and upper quartile. The Y-axis represents the percentage of accounts with a negative margin. Additionally, there is a blue reference line in the chart that represents Customer Data. This line corresponds to the average of the available customer data when drilling down into the details.

To access the detailed customer data by month, you can click on the blue line, which provides a drill-down option. In this detailed view, the customer data is presented. If the output value is negative, it is displayed as zero.

The purpose of this chart is to illustrate the revenue share generated by customer accounts that have a negative gross margin during the specified period. It calculates the ratio of revenue from accounts with a negative margin to the total revenue, providing insights into the price effectiveness after considering all price leakage.

In terms of interpretation, the chart indicates that X% of the revenue was contributed by customer accounts with a negative gross margin during the period under consideration.

These are calculated with revenue.

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Understanding the chart

The bar chart provides a visual representation of key performance indicator (KPI) data, specifically focusing on the percentage of transactions with a negative margin. The X-axis of the chart is divided into three separate bars, representing the bottom quartile, median, and upper quartile. On the Y-axis, the percentage of transactions with a negative margin is displayed.

In addition to the bar chart, a blue reference line is included, which showcases customer data. This reference line corresponds to the average of the customer data available when drilling down into the details. By clicking on the blue line, users can access more detailed customer data categorized by month. This will allow you to see if you are on a correcting trend by month as opposed to a general feel. It may happen that overall you might be doing better but month by month the trend might be telling a different story and you need to be aware of this.

For instance, take company X. While they seem to be working on improving their negative transactions percentage, you can notice that in fact, despite fluctuations, there is an ascending trend which is clearly detrimental.

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It is important to note that if the output value is negative, it will be displayed as a zero value. This ensures clarity and prevents confusion when analyzing the chart.

The primary purpose of this chart is to illustrate the revenue share generated by transactions with a negative gross margin during the specified period. This is calculated by dividing the revenue from transactions with a negative margin by the total revenue.

Moreover, this chart serves as a measure of price effectiveness, taking into consideration any price leakage that may have occurred. By examining the percentage of revenue generated from transactions with a negative gross margin, it becomes possible to assess the impact of pricing strategies and identify potential areas for improvement.

To interpret the chart, you can observe the percentage indicated on the Y-axis, which represents the proportion of revenue derived from transactions with a negative gross margin during the specified period. For example, if the chart displays "X% of my revenue came from transactions with a negative gross margin on the period," it signifies that X% of the total revenue was generated from such transactions.

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Understanding the chart

The bar chart is a powerful visualization tool that effectively displays key performance indicator (KPI) data. The Y-axis represents the percentage of per unit realized price increase. This chart provides valuable insights into the performance of the company's pricing strategy.

The blue reference line that displays customer data serves as a benchmark for comparison and allows users to gauge the effectiveness of their pricing strategies relative to customer expectations.

The value shown on the main chart corresponds to the latest available month of data. By drilling down into the chart, you can access detailed customer data on a monthly basis. This feature provides a more granular understanding of customer behavior and allows for targeted analysis and decision-making.

It is worth noting that if the output value is negative, it will be displayed as zero. This ensures that negative values do not skew the overall analysis and presentation of the data.

Overall, the chart effectively presents the actual average percentage increase of the realized price over a specific period. It enables you to analyze whether the realized price has increased or decreased in the last trailing twelve months. This information is crucial for evaluating the effectiveness of pricing strategies, identifying trends, and making informed pricing decisions to drive revenue growth.

This is calculated with number of deals.

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Understanding the chart

The primary purpose of this chart is to measure the percentage of deals that fall outside guidelines. Deals are considered outside guidelines when the InvoicePrice is less than or equal to the TargetPrice. In cases where no TargetPrice is provided, any deal that deviates from the default approval flow is considered outside guidelines. This information is vital for assessing the effectiveness of deal guidance and approval processes and can help derive corrective actions for improvement.

By analyzing the percentage of deals outside guidelines over time, companies can identify areas for improvement and make informed decisions to enhance their deal guidance and approval processes.

This is calculated on a simple average.

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Understanding the chart

The primary focus of this chart is to display the average number of days it takes for deals requiring approval to move from creation to approval. Deals that require approval are those that undergo an approval workflow and are not automatically approved.

By utilizing this chart, companies can effectively measure the effectiveness of their processes compared to industry standards. It provides insights into the efficiency of deal progression and highlights areas where process optimization may be necessary. The ability to identify bottlenecks and areas for improvement allows companies to streamline their processes, ensuring that deals move swiftly through the pipeline.

In summary, the bar chart displaying Deal velocity in days offers a visual representation of the time it takes for deals to navigate the approval process. By comparing these metrics to industry standards, companies can identify opportunities for process optimization, ultimately improving the efficiency and speed of their deal pipelines.

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Understanding the chart

The bar chart showcases Customer Data, providing valuable insights into the performance and behavior of customers. The value displayed on the chart corresponds to the average of the customer data available when drilling down into the details.

The main focus of this chart is to display the average number of steps a quote goes through during the approval process. Each step represents a stage or action within the approval workflow. By visualizing this information, companies can assess the efficiency of their approval processes and compare them to industry standards thus optimizing and streamlining the workflow to better reflect the need to quick quoting and deal management.

This analysis helps identify potential bottlenecks or inefficiencies, leading to enhanced productivity and smoother approval processes.

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Understanding the chart

The Standardized Waterfall chart serves as a powerful tool for analyzing customer data. The chart displays absolute values, providing a clear and accurate representation of the data. It offers two modes of operation to accommodate different analysis needs.

In Aggregated mode, price points are grouped into categories, allowing for a high-level overview of the data. This mode provides a consolidated view of the data, making it easier to identify patterns and trends across different categories.

The Drill down mode is designed for a more detailed analysis. It allows you to delve into subcategories, providing a comprehensive view of all price points and adjustments. This level of granularity enables a thorough examination of the data, facilitating deeper insights and precise calculations.

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The data considered for analysis is the trailing twelve months of transaction data. It is important to note that there may be a three-month delay in accessing the most recent data, as explained in the Plasma Dashboards - User Guide. This ensures that the chart reflects the latest available information and maintains anonymity.

By utilizing the Standardized Waterfall chart, you can gain valuable insights into your customer data. You can identify areas of improvement, such as price discrepancies or profit leakage, and derive corrective actions to address these issues. This tool empowers you to make data-driven decisions and optimize your pricing strategies, ultimately improving profitability and efficiency.

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Understanding the chart

This chart enables you to understand the structure of the product portfolio and how it relates to your revenue. In other words, it allows you to visualize the percentage of products required to cover a specific percentage of revenue within each decile, presenting a cumulative contribution.

By utilizing this chart as a Pareto analysis, you can gain a better understanding of your product portfolio's structure concerning revenue. It becomes possible to identify which products are driving the majority of the revenue and which may require improvement or attention.

To interpret the chart effectively, let's consider an example: "80 percentile: 20%." This statement indicates that 20% of the products generate 80% of the total revenue. This insight highlights the significance of a specific subset of products in generating a significant portion of the company's overall revenue.

This can vary as some businesses may have a wider selection of products and thus rank lower against their industry peers. Nonetheless, it will still give you valuable insights on potentially which products to prioritize.

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Understanding the chart

The Pareto chart provided illustrates the relationship between revenue and customers by displaying the percentage of customers needed to cover a certain percentage of revenue across different deciles and serves as a valuable tool for conducting Pareto analysis on customer contributions to revenue.

One example of interpreting the chart is that 20% of the customers are responsible for generating 80% of the revenue. This insight highlights the significance of a relatively small portion of customers in driving a large portion of the company's revenue.

This chart helps you recognise any imbalances in your customer portfolio. If a small percentage of customers are responsible for a significant portion of the revenue, it may indicate a lack of diversity in the customer base or a potential over-reliance on a few key clients. This awareness can prompt you to diversify your customer acquisition efforts and reduce your dependence on a small number of customers to mitigate risks.

Understanding this chart and how you position against industry peers allows you to make informed decisions and take strategic actions to optimize revenue generation and improve overall business performance.

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Understanding the chart

The chart presents key performance indicator (KPI) data. The main purpose is to illustrate the sum of revenue and provide insights into the company's position within the industry.

You can analyse the different bars representing the bottom quartile, median, and upper quartile, and gain a better understanding of where you stand in terms of revenue performance. The quartiles allow for a comparison against industry benchmarks or internal targets, indicating whether your company's revenue falls below, aligns with, or surpasses the industry average.

The inclusion of the blue reference line displaying customer data adds an additional layer of information. It signifies the importance of understanding the customer base and how it contributes to the overall revenue. By clicking on the blue line, you can access detailed customer data on a monthly basis, enabling further pattern, trends analysis, and potential areas for improvement.

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The total revenue chart highlights the significance of customer data and offers a drill-down option to delve deeper into the specifics of customer contributions to help yougain insights, make data-driven decisions, and identify opportunities to optimize the revenue generation strategies within the industry.

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Understanding the chart

This chart displays the number of unique products that have generated some revenue in the period shown. It enables companies to understand and compare product portfolio sizes strategy.

In this example we can see that company X is in fact doing really well, ranking in the top quartile with a steady number of products, reflecting a well designed strategy.

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Understanding the chart

Just as in the previous chart, here you can see where your main bulk of revenue comes from. The only difference is that in this case we are looking at which unique customer accounts generated transactions in the selected period.

The blue reference line your customer data and where you position against industry peers. In our example, again, Company X ranks in the top quartile.

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Understanding the chart

Similar in structure, this chart displays the number of unique people who managed transactions in the period shown. It enables you to understand and compare organizations. The less fluctuation you see here, the more stable your business actually is.

Moreover it can help, together with our Sales Compensation capability, to better reward your sales people.

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Understanding the chart

The chart fshows the average number of times a list price is increased per product. It provides valuable insights into how effectively benchmarked companies manage their price increases. The data for list price increases is captured from the local list price at the transaction level for specific product-customer pairs.

By analysing this chart you can understand the frequency of price adjustments and compare your practices with those of benchmarked companies, assessing your pricing strategies and determine whether they are in line with industry standards or need adjustments.

The chart's interpretation is straightforward: on average, a product's list price is increased twice within a trailing twelve-month period providing you with a benchmark to evaluate your own price adjustment frequency. You can assess whether you are implementing price changes too frequently or not frequently enough compared to the average.

Understanding the average number of list price increases per product is essential for effective pricing management. It helps you strike a balance between maximizing revenue and maintaining customer satisfaction. Too many price increases may lead to customer dissatisfaction and potential attrition, while too few increases may result in missed revenue opportunities or falling behind industry trends.

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Understanding the chart

As in the previous chart, you can see where you place among industry peers in the frequency of changing your prices per product. This allows you to understand to which extent prices are volatile within the industry or to which extent peers are managing their prices.

List price changes are captured from local list price populated at the transactions level for a particular product-customer pair.

Chart interpretation: On average, a product list price gets reviewed twice in the period that is trailing twelve months. In our example, Company X is not reviewing their product price nearly often enough.

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Understanding the chart

This chart displays the actual average percentage increase of the realized price in the period shown.

It enables companies to analyze whether the realized price has increased in the last trailing twelve months. It is an excellent tool to display how competitors are behaving, especially in volatile markets. In the light of this information, you can make informed decisions and adjust quickly to stay competitive.

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Understanding the chart

The chart presented focuses on illustrating the price increase leakage and serves as a benchmarking tool for evaluating the effectiveness of price increases compared to other companies. The data in the chart is expressed in percentages and revolves around the concept of list price increase and realized price increase. Note that in order to display a comparison waterfall in the chart, it is necessary to capture an increase in company data. In the absence of such data, the chart will only show key performance indicator (KPI) data, resulting in a simple waterfall representation.

The chart incorporates labels for on-invoice discounts, off-invoice discounts, and transaction costs which represent different factors contributing to the price increase leakage. Unlike some of the other charts in Plasma, the drill-down option is disabled for this particular chart, limiting the ability to access further detailed information or explore specific data points.

The chart can be interpreted the following way: Suppose the transactions data indicates that the list price has been increased by $1. This $1 increase serves as the index base of 100%. However, the realised price increase, which reflects the percentage of the price increase effectively passed on to customers, stands at 65%. This means that out of the $1 list price increase, only $0.65 was successfully conveyed to customers, so effectively, the dollar raise is in fact only partial.

By analysing this chart, you can gain insights into your price increase strategies and your ability to capture the desired price adjustments providing you an opportunity to implement improvements to enhance overall profitability.

This chart is calculated with the number of deals.

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Understanding the chart

The chart shows the percentage of deals that are required to go through an approval process. In this context, a "deal" refers to a submitted quote that has been approved.

The blue dotted reference line shows your data and where you position against industry peers.

The chart serves as a tool for evaluating the efficiency of the approval process. By tracking the percentage of deals that require approval, you can assess whether your processes align with industry benchmarks. If a high percentage of deals consistently require approval, it may indicate bottlenecks or inefficiencies in the approval workflow. On the other hand, a low percentage suggests a streamlined process where deals move swiftly through the pipeline.

The main aim here is to identify opportunities for optimizing processes. If your company's approval process lags behind industry standards, it may lead to delays in closing deals and potential revenue loss.

Optimizing the approval process offers several benefits. It reduces the time it takes for deals to move through the pipeline, improving overall sales velocity and increasing the likelihood of closing deals successfully. Faster approvals can also enhance customer satisfaction by providing timely responses and reducing customer wait times. Moreover, optimized processes contribute to increased revenue generation by minimizing delays and maximizing the conversion rate of deals.

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Understanding the chart

This chart displays the number of deals created in the selected period. A deal is considered to be a submitted and approved quote. The bigger number of closed deals the more likely you would rank in the top percentile and in this scenario, that is where you want to be compared to your industry peers.

The blue reference line illustrates where you place and it also allows for a more granular view (by month) if it is clicked on.

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Understanding the chart

This chart showcases key performance indicator (KPI), average deal size, which in this case refers to a monetized sum . The value displayed on the reference line corresponds to the average of customer data, which can be further explored through a drill-down option by clicking on the blue line. This drill-down functionality provides detailed customer data on a monthly basis.

The main focus of this chart is to display and benchmark the average deal size managed during the specified period in terms of revenue. Deals in this context refer to submitted and approved quotes.

Overall, this chart allows for a comparative analysis and provides insights into performance. Additionally, the drill-down option and the inclusion of customer data enable a more detailed examination of factors influencing the average deal size. By leveraging this chart, you can identify areas for improvement, align their deal sizes with industry standards, and make data-driven decisions to enhance revenue generation strategies.

Calculated as a simple average.

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Understanding the chart

This chart displays the average number of days that passed between the creation date and the submitted date, considering all deals. It enables you to measure processes effectiveness compared to the industry’s standards in order to identify the need for optimizing processes so that deals move faster through the pipeline.

Although the example shows a median quartile placement in the industry, there are major opportunities for improvement overall. The tendency here should be to position in the bottom quartile, meaning more deals in less time. This may point to a more streamlined approval workflow that would speed up the deal velocity from creation to submission to approval.