What is the Analytics page?

  • The analytics page is a page visible to the Admin side of the Organization. 
  • It provides real-time rich data about the organization which in turn provides actionable insights about the spend patterns of the organization’s employees, visibility into potential risks and much more. 

Why do we need the Analytics section?

  • Financial Control - Employee spends is the largest category of controllable expenses in an organization. With ample data, Fyle puts the control back into the finance team’s hands to influence company budgets and more.
  • Forecast Potential Risks - Fyle provides insights around most violated policies, top policy violators, expenses incurred during weekends or holidays, duplicate detections and more. This helps an organization tweak and manage its policies accordingly.

What is there in the Analytics section?

The Analytics page has 3 tabs:

  • Insights - This tab provides insights such as spend patterns across departments, business units, cost centers, expense categories, etc.
  • Operations - This tab provides insights on the turnaround times between different operations such as Fyle to Report, Report to Approval, Approval to Verification, etc.
  • Risks - This tab provides insights about policy violations, top spenders in the Organization, weekend expenditure, etc. 

Filters for the data

  • The insights provided in the Analytics page comes from real-time data of the Organization. 
  • The source data can be filtered by using filters such as time period, location, department, business unit, project, expense category, etc. 
  • By default, we show insights for the last two months. However, the base time period can be changed. Click on the FILTER + button next to the default date filter. 
  • You’ll now be able to change the date filter, add more filters or remove existing filters.
  • You can manually select the time period by selecting the From and To dates. Or you can consider choosing pre-defined time periods such as: This month, This quarter, This year, Last Month, Last Year, Last Quarter, Last 60 days, Last 120 days and Last 180 days. 
  • Click on the Plus (+) sign below the date filter to add a new filter. When you add a new filter, you must select:
  • Field- The field on which you want to filter the data. Eg: Department, Project, Location, etc.
  • Value(s) for the Field- The value(s) for the field used to filter the data. Eg: Bangalore, if the selected spend field is Location. This will filter the data for the selected time period and where Location is Bangalore. 
  • Similarly, more filters can be added. The insights will then be provided based on the filtered data. 

Let’s now look into each of the three Analytics tabs in detail.

Analytics Insights

Spend by Categories

  • This chart gives us the distribution of the organization’s expenditure based on the Expense Category. 

Spend by Departments

  • This chart gives us the distribution of the organization’s expenditure based on the Employee Department. 

Spend by Business Units

  • This chart gives us the distribution of the organization’s expenditure based on the different business units. 

Spend by Cost Centers

  • This chart gives us the distribution of the organization’s expenditure based on the different Cost Centers. 

Policy Exceptions

  • This chart gives us an idea about Policy Exceptions and the percentage of times an expense is approved despite the violation of a policy. 
  • For Example, 69% of the expenses on which the policy “Food < 100” was violated, still got approved despite the violation. 
  • This chart gives us an idea about whether certain policies must be retained or tweaked. 

Travel Planning - Flight

  • This chart provides us insight into how much total money was spent on Flight Expenses when Flights were booked within 7 days of the start trip as compared to those booked beyond 7 days of the start trip. 

Travel Planning - Hotels

  • This chart provides us insight into how much total money was spent on Hotel Expenses when Hotels were booked within 7 days of the check-in date as compared to those booked beyond 7 days of the check-in date.

Top Vendors

  • This chart gives us the distribution of expenses over the different vendors. 
  • This insight can help in planning for partnerships with the most frequently used Vendors. 

Booking Source - Flights

  • This chart gives us insight into the total money spent on booking flights when booked on their own by the Employees (Self) as compared to when booked by the Organization’s travel agent (Desk). 
  • This chart can help in planning for efficient partnerships with their booking agents. In case, the insights suggest that not a lot of Flights are booked via agents, then the organization can cancel existing partnerships with the agents. 

Booking Source - Trains

  • This chart gives us insight into the total money spent on booking trains when booked on their own by the Employees (Self) as compared to when booked by the Organization’s travel agent (Desk). 
  • This chart can help in planning for efficient partnerships with their booking agents. In case, the insights suggest that not a lot of trains are booked via agents, then the Organization can cancel existing partnerships with the agents. 

Booking Source - Hotels

  • This chart gives us insight into the total money spent on booking hotels when booked on their own by the Employees (Self) as compared to when booked by the Organization’s travel agent (Desk). 
  • This chart can help in planning for efficient partnerships with their booking agents. In case, the insights suggest that not a lot of hotels are booked via agents, then the Organization can cancel existing partnerships with the agents.

Analytics Operations

  • The top 4 numbers in this page indicate the average time that was taken for an expense to move between the different stages, during the selected time period.

Eg:- In the past 3 months, the average time that was taken between Fyling an Expense to Reporting it was 15 days. Similarly, the average time taken between Reporting an Expense and getting it Approved was 22 days. 

  • This page provides us with charts indicating the average time taken for an expense to move between the different stages, compared across different months. 
  • The time frame filters on this page are modular with respect to months, i.e., Past 1 month, Past 2 months, Past 3 months, etc. 

Turnaround Time - Fyle to Report

  • This chart provides us insights into the average turnaround time taken between Fyling an Expense to Reporting it, compared across the number of months selected in the time frame filter. 
  • In the above example, since the selected time frame was the Past 3 months, the average turnaround times compared across the last 3 months are shown. 
  • If the turnaround time in this chart keeps increasing, then it’s a call to use features like automated reminders which will automatically remind the Employees in periodic intervals to report their expenses.

Turnaround Time - Report to Approval

  • This chart gives us the average turnaround time taken between creating a report and getting it approved, compared across the selected number of months. 
  • If you observe that the turnaround time in this chart is increasing across months, then it would be useful to use automated reminders to remind the Approvers in periodic intervals to take action on the Fyled reports. 

Turnaround Time - Approval to Verification

  • This chart gives us the average turnaround time taken between Approving a report to Verifying it, compared across the selected number of months.

Turnaround Time - Verification to Reimbursement

  • This chart provides us insight into how much time on an average it is taking between the verification of the report and reimbursement of the money back to the employees. 
  • If you observe that the turnaround time in this graph is increasing across months, then you could probably reach out to the finance person for the Organization and investigate why it’s taking longer than usual to complete the reimbursement process. 

Analytics Risk

Risk Overview

  • This chart helps us understand high-risk factors like Policy Violations, Weekend expenditure, Fyling of duplicate expenses, etc. 
  • For Example, the above graph tells us that during the selected time frame, ₹4,769,052 came from expenses that violated some policy. Similarly, ₹10,535,961 came from expenses made on weekends, etc.

Top Policy Violators

  • This chart shows the top policy violators in the Organization along with the exact amount Fyled through policy violated expenses. Eg. Sranga is one of the top policy violators and has Fyled policy-violating expenses worth ₹1,446,224

Change in Spend - Categories

  • This chart provides insight into the percentage change in spending for the different categories. The percentage change is shown for the last month as compared to the month previous to the last month. Eg., Let’s say the above graph is viewed in the month of March. Then, there has been a 3755.30% increase in Hotel expenses in February as compared to January. 
  • This is a 2-sided bar chart, meaning if there was a negative percentage change for any of the categories, then the bar for it would be in the opposite direction indicating the negative change and would have a length proportionate to the magnitude of the change. 

Top Spenders

  • This chart gives us insight into the top spenders of the organization along with the exact amount spent by them. Eg., Vikas is a top spender who has spent ₹9,870,438 in total, in the selected time frame. 

Weekend Expenses

  • This chart provides us insight into the employees who spend the most on weekends. Eg., Sharath has spent ₹48,583 on the weekends during the selected time frame. 
Did this answer your question?