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Calculation Editor: Common Business KPIs and Scenarios

In an increasingly data-driven world, tracking and exploring key metrics is essential to staying on top of

evolving trends. In this guide, you will learn how to create calculations in a story to find metrics relevant

to your specific business by exploring fictional business scenarios and following step-by-step instructions

to create the following key performance indicators (KPIs):

• Time Aggregation Across Years (Quarter and Month)

• Year-to-Date

• Accumulative Sum/Running Total Across Time

• NPV and ROI

• Year-over-Year Growth

• Compound Annual Growth Rate (CAGR)

• Average Order Value

• Subtotal Percentage

• Sigma Level, Standard Deviation, Standard Error

• Attrition Rate

• Project Progress (%)

• Order Fill Rate

• Moving Averages Across Time

• Average Lead Response Time

• Ending Inventory Balance

Along the way, we will provide valuable resources to help you on your journey to becoming a data-

driven organization.

Creating a calculated measure in a story To create a calculated measure:

1. Select a chart in your story.

2. Navigate to the Designer > Builder panel.

3. Under Measures, select ‘+ Add Measure’ > ‘+ Click to Create a New Calculation’.

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Types of calculations • Calculated Measures: Perform a calculation on one or more measures

• Restricted Measures: Restrict the data from a measure so that it excludes certain members of

one or more dimensions

• Difference From: Find the difference in a measure's value between two points in time for a

single time dimension

• Aggregation: Create an aggregation such as sum, count, count dimensions, max, and max

• Date Difference: Calculate the difference between two-time dimensions

• Dimension to Measure: Create a measure by converting a dimension to measure.

Important Business KPIs

1. Time Aggregations Across Years (Quarter and Month) Visualizing sales performance over time is straightforward, but what if we want to compare quarter-on-

quarter performance across all years?

For organizations like Best Run Juice, a beverage retailer, it is important to identify seasonal trends to

focus production and marketing efforts during peak periods. To better understand these trends over a

longer time horizon, we would need to aggregate sales performance measures by quarter to find the

quarterly performance of all combined years. In this example, we will be using calculated dimensions

and nested “if” statements to investigate Best Run Juice’s quarterly performance for alcoholic drinks.

Steps To create a calculated dimension, select a chart in your story, then navigate to the Designer > Builder

panel. Under Dimensions, select Add Dimension > Calculated Dimensions > Click to Create a New

Calculated Dimension.

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In the calculation editor, we will be using IF and RIGHT functions to aggregate quarters. Within the IF

and RIGHT statement, type “date” followed by a period and “Calendar Quarter” (pressing Ctrl + Space

bar will display a list of suggestions).

Next, we will type 1 in the second input field to end the RIGHT function. To complete the IF logic, we will

set the condition field to =”1” and the true field to “Q1”. These steps will need to be repeated for the

other quarters by including a nested if statement in the false field. The final equation should look like

the image below.

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End Result The result is a combination column & line chart that shows the gross margin and quantity sold of

alcoholic beverages for the aggregated quarters.

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From this chart, we can see that Q2 is the highest performing quarter for alcoholic drinks across all

years. This highlights the spike in demand during the summer months, which is valuable information

when planning future marketing initiatives to exploit this seasonality trend.

While this example displays quarter-wise aggregations, the same steps can be used to create month or

day aggregations.

Additional Resources

• Formulas in SAP Analytics Cloud

• Conditional Formulas Using Dimension

• Calculated Dimensions Functions and Operators

• Calculated Dimension Video Tutorial

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2. Year-to-Date (YTD) Creating dynamic calculations like YTD or Month-to-Date (MTD) allows organizations like Best Run

Apparel, a clothing retailer, to compare company performance to past periods. In this example, we will

be using restricted measures to find current and past YTD values to assist with financial planning.

Steps Starting with a simple table outlining the sales revenue by product category, we will add a calculation by

selecting Account> more options>add calculations> restricted measure.

To create a dynamic YTD calculation, we will set sales revenue as the measure and order date as the

dimension. In values or input controls, select Current Period> To Date> Year.

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Next, we will create a previous year-to-date (PYTD) calculation by repeating the prior steps but altering

the Values or Input controls field. For this calculation, select Previous Period> To Date> Year.

We can then find the variance by creating a calculated measure to subtract PYTD with YTD.

Alternatively, you can select the PYTD and YTD columns and right-click to add a column to find the delta.

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End Result The resulting table displays YTD, PYTD, and variance calculations for the current system date of February

23, 2021. Through these calculations, Best Run Apparel can quickly identify that sales revenue for

clothing and footwear product categories have decreased compared to the same time last year.

Additional Resources

• YTD Calculations

• Compare YTD sales with previous YTD sales

• Custom Dates

• Creating Cross Calculations

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3. Accumulative Sum/Running Total Across Time Visualizing an accumulative sum is a common business requirement to understand a metric’s

progression over time. In this scenario, Best Run Apparel is looking to display the year to date sales at

the end of each month. We will be showcasing two methods to quickly create these metrics.

Steps

Time Calculations

In a bar chart displaying sales revenue over time, select the measure>more options> Add Time

Calculation> Year to Date

Table Calculations

Alternatively, we can achieve the same result in a table by right-clicking the sales revenue column> add

calculation> accumulative sum

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End Result Both methods yield the same result and calculate the monthly accumulative sum for an entire year.

Similar running calculations can be made on a quarterly or monthly basis as well. With this calculation,

Best Run Apparel can clearly see the sales revenue progression over time to track overall performance.

Additional Resources

• 4 Ways to Calculate an Accumulative Sum

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4. NPV and ROI During capital budgeting and investment planning, finding the net present value and ROI is essential to

analyze a project’s profitability. Best Run Smoothies is considering a one-time investment into new

blenders that could result in increased revenues for the next five years. We will be using calculated

measures and aggregations to find this project’s net present value and ROI.

Steps We will start by transforming the years into periods using if statements. Since the investment occurs in

2021, we will set this period to zero. The calculated measure should be formatted like the image below.

Since we do not have a discount rate available, we will use input controls to test different rates. Create a

calculated measure> Create new Input Controls> Static list> Add Values> select by range.

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Using the periods calculation and input controls, we will create a calculated measure to find the present

value of all future cash flows.

Next, we will use an aggregation to find the sum of all the present values.

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To find the NPV, we will add the sum of present values and the initial investment.

Lastly, we will calculate the ROI by dividing the NPV (benefit) with the investment cost.

To format the ROI to show as a percentage, select more options> format> deselect use unit of

underlying measures> change scale to percentage.

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End Result On the Discount Rate input control slider, we will set the rate to 10%. This yields a positive NPV result

and indicates that the projected present value earnings of the new blender investment exceed the

anticipated costs in present dollars. Moreover, an ROI of 188% suggests a high level of return for this

initiative. This is great news, but we also want to test other discount rates to get a better understanding

of different investment scenarios. If we set the discount rate to 15%, we see a decrease in both the NPV

and ROI. However, the investment remains attractive. Therefore, Best Run Smoothies should continue

with this project as the NPV and ROI suggest that this investment will be profitable.

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Additional Resources

• NPV and IRR

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5. Year-over-Year Growth One of the most important metrics is year-over-year growth as it provides a simple indication of positive

or negative performance when compared to the previous year. Instead of adding variances to a chart,

Best Run Apparel is looking to quickly compare 2020 and 2021 YOY growth.

Steps Starting with a sales revenue by order date bar chart, we will select sales revenue> more options> add

time calculation> Year-over-year.

We will edit the new Sales Revenue - YOY calculation and check the calculate as percentage box.

End Result By following these simple steps, we can find the YOY growth rate of 2020 and 2021. Best Run Apparel

can now visually compare the declining growth rates to gauge overall performance. The same steps can

be repeated to find period over period, quarter over quarter, month over month, and day over day

growth.

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Additional Resources

• Filtering Data by Time

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6. Compound Annual Growth Rate (CAGR) It is relatively easy to find the compound growth rate by navigating to a chart and selecting add CGR.

While this is incredibly useful, it only displays the growth rate as a trend line on the chart. Best Run

Apparel wants to understand its revenue growth over the past three years and display this information

as a point chart instead.

Steps To calculate the compound annual growth rate, we will need to create two restricted measures to find

the beginning and final values. In our case, the first year is 2019, and the last year is 2021. Next, set sales

revenue as the measure and order date as the dimension. In the values or input controls field, select by

member and choose the last year. Once complete, repeat these steps for the first year as well.

With the beginning and final values, we can create a calculated measure to find CAGR.

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End Result We were able to replicate the compound annual growth rate for sales revenue over the last three years

and displayed this information via a point chart. This calculation can be updated to find the compound

growth rate over different time periods and hierarchies. Based on the relatively small CAGR, Best Run

Apparel can expect stagnating future sales.

Additionally, you can also calculate YOY growth by using the same steps to create a restricted measure

for 2020 and 2021. Simply, update the calculated measure to (2021 revenue -2020 revenue / 2020

revenue) *100.

Additional Resources

• Compound Growth Rate to Track Progress

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7. Average Order Value In this scenario, the active lifestyle brand, Best Run Fitness, is selling its exercise clothing products across

a variety of different partner stores and wants to understand which partners to prioritize. By

categorizing its partners into studios, gyms, or general apparel stores, Best Run Fitness can better

understand each group’s performance by calculating the average order value. This metric will assist in

evaluating and planning marketing and pricing strategies that directly influence revenue growth. In this

scenario, we will be utilizing calculated measures and dimensions to find the average order value.

Steps We will begin by categorizing the partner stores into three groups by creating a calculated dimension

with IF and RIGHT functions. Within the RIGHT statement, type “Store” followed by a period and

“description” and close it off by adding a 6. To complete the IF logic, we will set the condition field to

=”Studio” and the true field to “Studio”. We will repeat these steps for the Gym category. The final

equation should look like the image below.

To finding the count of all orders, create a calculation> aggregation> Count Dimensions as the

Operation> Order ID as the Aggregation Dimension.

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Afterwards, create a calculated measure and divide Sales Revenue with Count of Orders.

End Result This resulting bar graph shows the average order value by store group. While the number of orders for

Studios is minimal, we can see that it has the highest average order value. With this information, Best

Run Fitness can evaluate these different categories and update its pricing and marketing strategies

accordingly. Using the count dimensions aggregation, similar KPIs such as average customer revenue or

customer acquisition cost can be created.

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Additional Resources

•

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8. Subtotal Percentage Currently, users can quickly calculate the grand total percentage by using built-in functions. However,

during planning, users may also require subtotal percentage calculations. To cut costs, Best Run Apparel

is looking to discontinue one product type within each product category. To help identify poor sales

performers, they would need to calculate the subtotal percentages for each product type. We will be

using restricted measures with constant selections to create these calculations.

Steps We will start by creating a restricted measure> sales revenue as the measure> product category as the

dimension> select all categories in the values or input controls field> enable constant selection> set

product as the constant dimension. The restricted measure value will remain fixed for all members

specified in the constant dimension.

Next, create a calculated measure by dividing sales revenue with total revenue.

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Format this calculation by selecting more options> format> deselect use unit of underlying measures>

change scale to percentage.

Lastly, we will format our table like the image below. Select each individual product in the filter to

ensure total values are excluded.

End Result With the subtotal percentage calculation, Best Run Apparel can create a table to identify unpopular

product types. We can see that headgear, bottoms, and outdoor shoes are performing the worst in their

respective product category. With this calculation, Best Run Apparel can make an informed decision

when choosing which product lines to discontinue. Using restricted measures and constant selections,

you will be able to create a variety of % share calculations.

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Additional Resources

• Restricted Measures with Constant Selection in SAP Analytics Cloud

• Having a dynamic % Share of total using Restricted Measures with Constant Selection

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9. Sigma Level, Standard Deviation, Standard Error When manufacturing intricate parts, maintaining six sigma quality will help businesses discover and

eliminate production defects. In this scenario, Best Run Watches is manufacturing watch gears and

wants to ensure that the initial production run meets the acceptable quality levels. With precise

equipment like watches, there is little room for error, and manufacturers need to be aware of the strict

size tolerances when producing small components.

We will be analyzing Best Run Watches' premium and entry-level product lines, which require different

specification limits. For the premium line, the lower level specification limit for watch gears is 0.250mm,

and the upper limit is 0.450mm. The entry-level line is more lenient and will require a 0.220mm lower

limit and 0.470mm upper limit.

We will be using input controls and calculated measures to create key metrics such as sigma level,

standard deviation, and standard error to help Best Run Watches manage the quality of its

manufacturing process.

Steps We will start by creating an aggregation calculation to find the standard deviation of gear sizes. Set

standard deviation as the operation> Tested Size as the measure> manufacturing ID as the aggregation

dimensions.

Next, we will calculate the average gear size using an average aggregation calculation.

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After you have this, we will create two calculated measures to subtract the lower specification limit from

the mean and subtract the mean from the upper specification limit. By adding input controls, we can

alter the upper and lower limit values to meet the acceptable quality levels for a specific product line.

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We will create an IF function to identify the smallest limit value and divide that with the standard

deviation to find the sigma level.

We can also quickly calculate the standard error by finding the count of gears and using the previous

standard deviation calculation.

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End Result The values shown in these charts provide Best Run Watches with a clear overview of its production

capabilities. The low standard deviation value indicates a relatively precise manufacturing process as

most of the produced gears are clustered around the mean. This means that there is low variability in

the size of produced gears resulting in a consistent product.

For the premium product line, Best Run Watches falls short of the ideal six-sigma benchmark. While the

current sigma level is satisfactory, more can be done to improve the quality. However, if we consider the

entry-level line, which has more lenient limit standards, we can see that the six-sigma level is met.

Therefore, this metric allows Best Run Watches to create different specification limit scenarios for each

of its product lines to gauge the precision of its production capabilities.

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Additional Resources http://www.miconleansixsigma.com/six-sigma-calculation.html

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10. Attrition Rate To keep track of employee churn, companies will need to manage key metrics like attrition rate. In the

current unpredictable landscape, it is more important than ever to understand the number of vacant or

eliminated positions in an organization. In this example, Best Run Smoothies laid off a significant portion

of its staff due to the pandemic and wants to understand its current employee attrition rate. We will be

creating several calculated measures to find the annual attrition rate.

Steps We will start by finding the total number of employees through a count dimensions aggregation. This

will count all inactive employees and new hires on record.

We will use a restricted measure to find the number of employees who left the organization in the past

year by restricting the leave date to 2020.

We will repeat the same process to find the number of new employees who joined the organization by

restricting the join date to 2020.

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We can now find the opening employee balance by subtracting the total employee count by the number

of new hires.

Similarly, we can find the ending employee balance by subtracting the total employee count by the

number of employees who have left.

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Finally, using the previous calculations, we can find the annual HR attrition rate. We will also format this

attrition rate to display as a percentage.

End Result The result is a point chart with an annual employee attrition rate of 49.28%. Due to the spike in

terminated employees in the first quarter of 2020, this rate is significantly higher than expected. As a

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small organization, this metric will help Best Run Smoothies manage its future headcount planning to

minimize major changes in employment.

Additional Resources

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11. Project Progress (%) When launching new initiatives, keeping track of the overall project progress is essential to deliver

results on schedule. In this scenario, Best Run Bikes is looking to open a new retail location but is

concerned about having the store ready in time for the soft launch. While this information is usually

managed through project management software, we will showcase how we can create this same metric

on Sap Analytics Cloud by utilizing date difference and aggregation calculations.

Steps Our current project plan only contains the task, planned start/end dates, and percentage of tasks

completed. So, our first step would be to calculate the planned duration of each task using a date

difference calculation.

Next, we want to find the number of days worked on each task by creating a calculated measure to find

the product of planned duration and percentage completed.

To find the total amount of days in progress for all tasks, we will create a sum aggregation calculation.

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With all the prior calculations completed, we can now divide the total task progress with the planned

duration to find the project progress percentage. We will format this to show as a percentage.

End Result With numerous competing tasks at different stages of completion, Best Run Bikes can use this metric to

understand the overall progress of the new store launch. As there are only a few months until the soft

launch, Best Run Bikes will need to carefully manage its resources if it wants to complete the project

within schedule. This metric provides a clear overview of the project progress to help project managers

plan and adjust activities.

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Additional Resources https://www.aceproject.com/help/how-is-project-progress-calculated/

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12. Order Fill Rate In a world moving towards online shopping, it is now more important than ever to ensure that your

business is properly managing its inventory levels. When a product is purchased, the order should be

fulfilled immediately so it can arrive on-time without any delays. In our example, Best Run Apparel is

looking to find the order fill rate to better manage inventory levels and get products to consumers

faster.

Steps Start by finding the total number of orders placed by creating a count dimensions aggregation.

Next, we will create a restricted measure to find the number of orders shipped in full. We are assuming

that all products delivered on-time were filled completely while the rest were delayed due to

warehousing or inventory delivery issues.

We can calculate the order fill rate by dividing the number of filled orders by the number of total orders.

We will format this to show as a percentage.

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End Result The resulting order fill rate is well below Best Run Apparel’s expectations. There are a variety of

inventory or warehousing issues that could have contributed to this result. To maintain customer trust,

Best Run Bikes will need to continually track and work to improve this metric.

Additional Resources

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13. Moving Averages Across Time In our scenario, Best Run Shirts, a custom t-shirt start-up, buys fabric in bulk each month and is looking

to understand the changing supplier prices by calculating the moving average. This will smooth the data

and allow them to identify price trends to support its raw material purchasing. We will be using table

calculations to find the moving average of Best Run Shirts’ supplier expenses.

Steps Start by creating a table to analyze the supplier expenses for each month.

Select each individual month in the date filter. This ensures that the total values are excluded (the total

values can interfere with the moving average calculation).

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Next, right-click the gross margin column to access more options>add calculation> moving average.

End Result The resulting table showcases the moving average of Best Run Shirts’ supplier expenses for 2020. With

this information, they will be able to create a clearer picture of price trends to assist with their

purchasing plans.

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Additional Resources

• Creating Calculations from Table Rows or Columns

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14. Average Lead Response Time Calculating the average lead response time provides an indication of the time it takes for a sales

representative to follow-up on a lead. In this scenario, Best Run Graphics is looking to gauge the

performance of its sales department by finding the average lead response time. The current process for

customers interested in graphic design services is to first enter their contact information into the

website for a consultation.

Our goal is to find the average time it takes the sales team to contact the customer once this

information has been entered. We will be using aggregation and date difference calculations to find this

metric.

Steps We will start by finding the total number of customer leads using a count dimensions aggregation.

Next, we will use a date difference calculation to find the number of days it took the sales

representative to reply to a consultation request.

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Lastly, we will divide the days to respond by the number of leads to find the average lead response time.

End Result The result is a horizontal bar graph displaying the average lead response time for each sales

representative. These average lead response times are much longer than expected and could discourage

prospective customers from using its services. To maintain interest and provide timely service, Best Run

Graphics may need to hire more sales representatives to assist with the outreach process and decrease

the current lead response times.

Additional Resources

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15. Ending Inventory Balance In the next month, Best Run Watches is expecting an unusually large order and needs to calculate its

ending inventory to decide if its current planned production levels need to increase. However, the total

amount of sales for the month has not yet been determined. Thus, we will be using calculated measures

and input controls to forecast COGS and find the ending inventory balance.

Steps We will start by creating the calculation input control to estimate the COGS.

With this input control, we will create a calculated measure to find the ending inventory.

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To predict the ending inventory for December 2021, we will set the chart filter to November 2021. This

will ensure that the calculation includes the correct beginning inventory.

End Result Best Run Watches estimates that the December COGS will be approximately $78,000. Setting the input

control slider to that estimate, we find that we have an ending inventory value of just under $180,000.

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However, the upcoming bulk order requires $50,000 of inventory, and it is company policy to maintain a

safety stock value of $150,000. Thus, to maintain adequate inventory levels, Best Run Watches will need

to increase production.

Additional Resources

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