Optimizing Receipt Management for Efficiency and Impact for sales and financil department

Optimizing Receipt Management for Efficiency and Impact for sales and financial department

Optimizing Receipt Management for Efficiency and Impact for sales and financil department

Optimizing Receipt Management for Efficiency and Impact for sales and financial department

Scenario

The financial team of a large Brazilian multimodal logistics company sought to address some issues they had in the sector. Currently, they manage receivables from their customer portfolios weekly in spreadsheets, a laborious task that is necessary due to lack of automation. Additionally, they are responsible for presenting updated information to the company's board, where a team member is in charge of collecting, reviewing, and producing the presentation on time.

Goals

  • Automate processes

  • Reduce human errors in the process

  • Decrease fragility

  • Reduce average user time on activities

  • Eliminate employee task overload

The Analysis

CSD Matrix

Certainities

Monthly manual update for month-end closing

Certainities

Monthly manual update for month-end closing

Suppositions

The segments we have in the database will remain the same (to be reviewed)

Data will be input manually

Suppositions

The segments we have in the database will remain the same (to be reviewed)

Data will be input manually

DOUBTS - DOUBTS - DOUBTS - DOUBTS -

How will we receive due date data for accounts receivable?

Is it necessary to map tables in the database to validate the data?

What are the rules for setting monthly and annual targets?

How to determine if the data is litigated, non-litigated, or intercompany?

What are the rules for defining services and on-demand purchasing services?

How does the logistics mesh overdue evolution chart work?

What are the month-end closing rules?

What are the rules for generating charts?

What will trigger the due date?

What are the rules for displaying companies in the evolution?

For users, is it more valuable to view the closed or current month?

Mapping

Understanding the delimitation of discovery

How will the solution help the persona?

Providing updated information about accounts receivable

Antecipate topics related to subject

Optimize the persona's time spending doing daily activities

Automatize the process

Reduce human errors

Personas

C level

Supervisors

Analysts

Frequency

Daily

Monthly

Which tasks does the user will do using the solution?

Critical analysis about provided data

Export to other formats

Publishing details for board and strategic sections of company

Input of data

Financial control of debts

Mapping

Understanding the delimitation of discovery

How will the solution help the persona?

Providing updated information about accounts receivable

Antecipate topics related to subject

Optimize the persona's time spending doing daily activities

Automatize the process

Reduce human errors

Personas

C level

Supervisors

Analysts

Frequency

Daily

Monthly

Which tasks does the user will do using the solution?

Critical analysis about provided data

Export to other formats

Publishing details for board and strategic sections of company

Input of data

Financial control of debts

Scenario analysis

Analysis as-is today

To dive deep in the solution, we made an analysis of the current presentation the users need to prepare. The full analysis it's not in the case due the confidentiality terms.

Open values - open bills tree

  • They present the open accounts monthly for review

  • There is no specific information regarding the data source

  • Overdue dates are not standardized

  • They work with three main branches: judicialized or not and special accounts

  • There is no standard for special accounts, as they are based on customer relationships or special cases

  • The values are all above R$100,000; otherwise, they are considered special cases

  • There is a standard for overdue data: less than 2 years, between 2 and 5 years, more than 5 years

  • They follow the rules of IFRS 9.

Financial cash protection

  • They have overall insights from the month, separated by general and type of services

  • They need the evolution of the month

  • They gather information from all types of services and present them to the C-level

  • They have a default goal, and it is divided by overdue of the month and the total accumulated

  • They need to inform the gross revenue to generate the goal

  • They identify customers with the most open overdue bills and those who pay the most

  • They create a comparative vision of the year with the previous year

  • They need a vision for delinquency by type of services, with the possibility of an extended view

  • They need to have a view of customers with the most open overdue invoices.

The Solution

Prototype and final solution

The solution was created with collaboration of users, board and team. Developed to reduce the effort of sales team, the fragility of information and the security of data.

Access the prototype

Before the discovery, users conducted analysis on a single main segment, a time-consuming and challenging activity. However, with a unified database solution, it became possible to access all data and filter it by segments.

Two visions were created: a simple one and a comprehensive one with more data and graphs, tailored to address various needs identified during user interviews.

Throughout the process, it was noted that users often repeated information to achieve the same goal. To improve analysis, a graph was developed to consolidate and merge this redundant data.

Consistent color usage is employed to represent similar types of information.

A study was conducted to determine the most effective types of graphs for different kinds of information.

Upon viewing the solution, users expressed great satisfaction and requested enhancements, such as additional information in certain graphs.

This innovative approach was only achievable due to the single database solution, streamlining data search, filtering, and maintenance processes for users.

Takeaways

To simplify the process, unifying the database enables users to provide only two data inputs: the end-of-debts provision percentage and the default reduction goal, sourced from another company's instance.

Upon document analysis, it was observed that certain percentage information overlapped but varied based on time frames. To streamline input, two stages were introduced. The first stage focuses on the current month, with all time frames separated and a comprehensive view of the month that can be modified by the user as needed.

The second stage involves inputting data for the following month, reducing user effort by implementing range input. This allows users to input the same percentage for various time frames, which the system then separates into their respective zones.

Another crucial input for users is special cases. A dedicated section was created for this purpose, enabling users to add, edit, and delete these cases as necessary.

For this discovery we saw that with the improvements the results will save 2 hours per week to every user of sales team and 1 week of the main user by month.

To simplify the process, unifying the database enables users to provide only two data inputs: the end-of-debts provision percentage and the default reduction goal, sourced from another company's instance.

Upon document analysis, it was observed that certain percentage information overlapped but varied based on time frames. To streamline input, two stages were introduced. The first stage focuses on the current month, with all time frames separated and a comprehensive view of the month that can be modified by the user as needed.

The second stage involves inputting data for the following month, reducing user effort by implementing range input. This allows users to input the same percentage for various time frames, which the system then separates into their respective zones.

Another crucial input for users is special cases. A dedicated section was created for this purpose, enabling users to add, edit, and delete these cases as necessary.


For this discovery we saw that with the improvements the results will save 2 hours per week to every user of sales team and 1 week of the main user by month.