From the homepage, you can select the module that you are interested in exploring by using the buttons found at
the top of the main visualisation panel. These modules are; Benefits, Reimbursements, User
Activity and Workforce.
Once you have selected a module, you can jump into it by using the See More button at the bottom of the
panel. This will take you to the module landing page.
Modules of Darwin Analytics Centre are made up of different pages. Once you have entered a module, page names
are displayed across the top of each page, beneath the module title. Click the names of these pages to navigate
into them and view the content.
You can return to the homepage, by clicking the home icon on the top menu bar, or by clicking on the MercerMarsh
Benefits logo in the top left of the page.
To access navigation in the sidebar, click the burger icon (three horizontal lines) on the top of the vertical
blue sidebar on the far left of the screen.
This action expands the sidebar and shows the Menu, with four buttons displaying the four module titles.
Clicking these buttons will direct you to the landing page of the respective module.
Please note that selections you have made in the main filter set will carry with you while navigating through
Darwin Analytics Centre.
Clicking on the burger icon again collapses the sidebar.
When in a detailed content page of a module (i.e any page other than a scenario or summary page) you can use
quick access functionality to jump directly to different sections of that page.
The sections making up content pages are; Time, Geography, Organisation,
Demographics and Cross Analysis.
Quick access links are listed under the Quick Access heading beneath the navigation buttons in the
sidebar.
This functionality is only available on content pages and so will not be present on Summary or Scenario pages.
To access the filter section, select the filter icon on the sidebar.
Individual filters are grouped together under the headings; Time, Geography, Organisation
and Demographics, followed by any section specific filter headings.
To make a selection in a filter, open up the filter group and click on the filter to display a drop down menu.
Select the values you are interested in and then click the submit button to apply these selections to your data.
Once submitted, you will see a number appear in the filter indicating how many selections you have made in that
field.
Selections made in filters will affect the values available in other filters. For example, if APAC is selected
in the region filter, only APAC countries will be available to select in the Country filter.
Within the tool there are certain fields that have a mandatory selection. There must be selections in the Time
filters and a currency must be selected in the Currency filter of the Geography group. Default values will be
selected in these filters initially, but can be changed in the same way as any other filter.
To view the selections you have active in your filters, click on the light blue “Selections” button on the top
right hand corner of the screen.
To remove all filters selections, click on the reset selections button in the filter section of the
sidebar. This action will remove all current selections and return mandatory filters back to their default
values.
To create a comparison, open up the filter menu by clicking the filter icon on the sidebar and then select the
Click to Compare button.
This creates a comparison data set that you will see applied to visualisations. This comparison will
automatically default to the same filter selections in the main filter set.
To filter the comparison data set, use the comparison filter set which appears beneath the main filters. These
filters are presented and work in the same way as the main filter set.
To see the selections you have made on your comparison data set you can use the Selections box in the top
right of the screen.
Clicking the Reset Comparisons button on the sidebar will reset the comparison filter values to the same
state as the main filter set.
To remove the comparison dataset from visualisations, click the Remove Comparison button.
Please note that there are two filters in the main filter set that apply to both the main data set and the
Comparison data set. These are Currency and Timeframe. If you want to change these filters this
must be done in the main filter set.
To access the Persona selection area, click the Persona icon on the sidebar.
With the menu expanded you will see four different persona headings; Age Band, Gender, Length
of Service and Marital Status.
Expanding these headings will enable the selection of individual personas.
Selecting a persona will make selections in the filter it applies to. For example selecting the Adult
persona under the Age band heading will select the 31-35, 36-40 and 41-45 age band
categories in the Age Band filter of the main filter set.
You can see these selections in the Selections display panel.
Selecting a persona in the same group will overwrite the selection in that group. For example, selecting
Young Adult will deselect Adult. However, selections across multiple different personas can be
made; for example, Young Adult and Male.
Having made a persona selection you can then interact with the main filters themselves to alter the selections.
This will, however, clear the originally selected persona.
To clear all personas selections click on the Clear Personas button on the sidebar. This will clear all
filters affected by the personas.
Use the scroll functionality on table visualisations to adjust the view and display additional rows or columns.
This can be done using either the scroll bar that exists on the visualisation, the scroll wheel on your mouse,
or clicking into the table itself and using the arrow keys on your keyboard.
On any graph where the data extends past the size of the visualisation, a scrollable mini chart will appear
summarising the entire content either on the side or the bottom of the visualisation. Scrolling within this
window will allow you to drag across to see the hidden data.
Executive Summary Reports can be configured from the home page by selecting the Configure Report button
under the Executive Summary Report heading.
When the Executive Summary Report overlay appears you can choose between summarising benefits or reimbursements
data. Having selected between these you can then choose to run the report globally or locally. A global report
will display data against countries, whereas a local report will display data against the departments in a
single country.
The reporting overlay can also be opened by selecting the reporting icon on the menu banner. This can be
accessed from any page of the product.
Once you have configured your report, click the Generate Report button.
The report will be generated in the background before being downloaded to your device in PDF format.
When on a page where the measure or dimensions can be changed, you can click on the Measure Select or
Dimension Select button at the top of the page to list the applicable options.
Switching between these options changes the content of visualisations on the page.
You can switch between measures on most content pages.
Switching between selections in the Measure and Dimension Select windows has no effect on selections in the main
filter set.
Please note that the measure select window will display “Measure Selection is not currently available” on pages
where this functionality is not applicable; e.g. The Home Page.
Predictions are estimates of future events based on existing data.
We use an ensemble forecasting approach that combines several methods—such as
ARIMA, SARIMA, and Exponential Smoothing—to enhance accuracy.
Our visualisations present forecasted trends for the remainder of the
calendar year. For example, if you are eight months into the year (August), you
will only see four months of predictions (September, October, November and December).
The confidence we have in our future predictions is based on a comparison of
historical predictions against actuals. We assess the accuracy of our model
regarding historical values by using MAPE (Mean Absolute Percentage Error).
This ensures that we present only predictions with a high level of confidence.
The Country filter in the main filter set will not affect these visualisations.
Scenario pages allow you to view the effect that a change of a measure has on your cost.
Scenario pages are available in the Benefits and Workforce modules. The Benefit scenario page
looks at utilisation rate and the Workforce page at headcount.
These pages consist of a table with a dimension that can be changed using the Dimension Select functionality.
Employer Cost and the page specific measure columns follow this.
The final column in the table is labeled Custom Potential Employer Cost. This measure shows the potential
employer cost value when the page specific measure is modified.
The page specific measure can be modified using the custom input box on the top right of the visualisation. To
apply the custom value, enter your value and press Enter.
If we take the benefit utilisation scenario page as an example, you can see what your current cost is, what the
utilisation rate is and what the employer cost would be for your custom rate if all other things are equal.
Using cross analysis visualisations you can interrogate your data across multiple dimensions simultaneously.
Cross analysis visualisations contain two filter options on the top right hand side of the visualisation. Open
the drop downs, select your dimensions and they will be applied to the table.
Use the total option in the dimension drop down if you want to see the data against a single dimension.
The measure displayed in Cross Analysis tables is dependent on the measure selected on the page with the Measure
Select functionality.
Please note, these visualisations are affected by filters in the main filter set as normal.
View glossary terms and definitions for clarity on how to interpret details of Darwin Analytics Centre.
Active Benefits
Total number of uniquely named benefits with an eligible population in the selected time-period
Employees with Benefit
Total number of unique employees who have selected at least one benefit.
Eligible Population
Number of distinct employees that are eligible to select a benefit. This means that they fit all the requirements such as length of service, salary etc. that are set up in Darwin as benefit selection rules.
Total Selections
Total number of selections made by all employees per benefit.
Utilisation Rate
Percentage of the eligible population that have selected a benefit/group of benefits.
Employer Cost
Employer contribution towards the benefit cost. / Amount spent by employer on the benefit cost.
Employer Cost per Head
Employer contribution towards the benefit cost divided by the eligible population / Amount spent by employer on the benefit cost divided by number of employees who could have the benefit.
Employer Fringe Rate
The total amount spent on benefits by the employer expressed as a percentage of employee base salary (e.g. £1,000 employer benefit cost versus a £10,000 salary would be a fringe rate of 10%).
Employee Cost
Employee contribution towards the benefit cost / Amount spent by employee on the benefit cost.
Employee Cost per Head
Employee contribution towards the benefit cost divided by the eligible population/ Amount spent by employee on the benefit cost divided by number of employees who could have the benefit.
Total Costs
Total benefit cost summing up employer and employee contributions.
Total Costs per Head
Total benefit cost summing up employer and employee contributions divided by number of employees who could have the benefit.
Approved Reimbursements
Total number of approved reimbursement claims.
Approval Rate
Percentage of reimbursements claims that were approved as a proportion of those submitted.
Approved Reimbursements per Head
Total number of approved reimbursement claims divided by number of eligible employees.
Reimbursed Amount
Total cost value of approved reimbursements.
Reimbursed Amount per Head
Total cost value of approved reimbursements divided by number of eligible employees.
Login Rate
Percentage of the workforce that has logged in at least once. We calculate login rate by looking at the number of unique logins divided by the headcount we have for that period. If the login rate is 50% and the population is 100 then 50 people have logged in at least once.
Total Logins
Total number of logins counts all the instances an employee logged in, so again in our scenario if 50 people each logged in twice then the total number of logins would be 100.
Logins Per Head
Total number of logins per employee. The calculation is total logins divided by headcount for that period.
Interaction Rate
Percentage of employees who have made at least one change/transaction within Darwin. This change could be a benefit selection/deselection, changing a benefit level, adding a dependent or a beneficiary.
Total Interactions
Total number of changes/transactions within Darwin.
Interactions Per Head
Total number of changes/transactions per employee regardless of whether they have logged in.
Total Campaigns
Total number of campaigns sent using the Darwin campaigns tool (if one campaign was sent to 10 people, the total number of campaigns will be 10).
Headcount
Total number of employees recorded on the last payroll close date.
Joiners
Total number of new employee records within the payroll period.
Leavers
Total number of employees with a confirmed leaving date within the payroll period.
Attrition Rate
Percentage of headcount that have been identified as leavers.
Predictions
Predictions are estimates of future events based on existing data.
We use an ensemble forecasting approach that combines several methods -
ARIMA, SARIMA, and Exponential Smoothing - to enhance accuracy.
This method leverages the historical performance of each technique to create
reliable forecasts while accounting for trends and seasonality.
Benchmarking
Clients who have agreed to the analytics clause in their Data Processing Addendum (part of their contract) will be able to access Benchmarking. We use de-identified data from over 240 Darwin clients that have agreed to this in their contract to provide comparisons with your own data, to answer the question ‘How do I compare with others?’
Five areas are currently available: Login Rate, Logins Per Head, Reimbursement Approval Rate, Approved Reimbursements per Head and Attrition Rate.
You will need to select a country and Month/Year that you wish to compare against.
There are two types of benchmarking - Median based benchmarking and proportional benchmarking.
Median Benchmarking
The median benchmarking displays your figures, for example your login rate, against the median value of the benchmarked group. The median is the middle value if they were all sorted from smallest to largest.
Proportional Benchmarking
The proportional benchmarking displays your relative position as a point on the graph, in comparison to all the other benchmarked Darwin clients for that country. We also display your value for those metrics as a percentage of the highest value we have for that country and time period.
Scenarios
There are two scenarios that you can use within DAC: the utilisation rate scenario and the headcount scenario that show the potential employer cost.
Utilisation Rate Scenario
The utilisation rate scenario allows users to input a custom utilisation rate (up to 100%) and see what the employer costs for that period would have been if no other variable had changed (headcount, costs etc.).
This is done using a proportional multiplication. An increase in the utilisation rate from 50% to 60% would see costs increase by 20% as that is the proportional change.
Headcount Scenario
The headcount scenario allows users to input a custom percentage change (including negative percentage change) in the total headcount and see what the employer cost would have been for the same period if no other variable had changed (utilisation rate, costs etc.).
This is done using a simple multiplication. A 10% increase in headcount would see a 10% increase in employer benefit costs.
Exchange Rates
All costs are reported in local currency in Darwin and we use exchange rates that we download from a trusted online global exchange rate source and are ingested into our database on a daily basis.
We then calculate the rate between each local currency in the database, and the main currencies we support (USD, SGD, GBP, EUR, CNY).
During the monthly update of the data in Darwin Analytics Centre, the figures are aggregated to a monthly, quarterly and yearly level. We then apply the currency conversion to those aggregated figures.
The exchange rate date is set as the following:
For monthly aggregations, the date is the first of the month.
For quarterly aggregations, it's the first date of the quarter.
For yearly aggregations, it's the first date of the year.
In other words - the yearly aggregate figures for 2024 will have been converted using the exchange rate as at 1st January 2024.
Data Availability
Client Selection
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Changing Timeframe will reset all of your filters and set date selections to the most recent
available.
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You are trying to select a Region while having a Country or Local
Currency selected.
Selecting a Region will reset the currency to
GBP and clear the Country filter.
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Region?
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Warning
You are trying to select a Region while having a Country or Local
Currency selected.
Selecting a Region will reset the currency to
GBP and clear the Country filter.
Are you sure you want to select a
Region?
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Generate Report
Select a report to generate
Reimbursements unavailable with current filter selections. Please make
different selections
Select a global report summarising data at a country level, or a local report summarising data at a
department level for an individual country
Select a local country. This will overwrite Region and Country selections in the main filter set
Time, Currency and Business Unit (if available) filters are set in the sidebar
Region and Country filters are also set in the sidebar, unless overwritten by a local country
All other filters from the sidebar DO NOT affect the report
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