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Automating Profitability Assessments for Smarter Business Decisions

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Industry: Business, Finance

Highlights

Need

The customer wanted to automate profitability assessments across various business parameters in order to optimize decision-making processes.

Solution

A comprehensive platform using time-driven activity-based costing to automate profitability assessments.

90%

reduction in monthly efforts on profitability assessment

2x

faster decision-making

In collaboration with Hymux Technologies, the customer received a fully-fledged platform that automates profitability assessment across multiple parameters, such as revenue, costs, net profit, resource capacity, and utilization. The solution is capable of gathering, processing, and analyzing business-specific data from various sources, including enterprise resource planning systems, performance management applications, and customer relationship management systems.

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Victoria Rokash
Business Development Manager

Customer

The customer is a provider of profitability and cost management solutions, based in Finland. The company was established as a spin-off from one of the largest universities in the country and offers enterprise-grade systems to businesses across various industries, from manufacturing to finance.

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Solution

Engineers of Hymux Technologies delivered a solution to assess business profitability that makes use of the time-driven activity-based costing methodology. The system comprises the following components:

  • Process modelling
  • Data integration
  • A calculation engine with dynamic equations for processes
  • Report generation
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How it works

The solution covers unlimited business dimensions (customer, product, vendor, order, line item, etc.),as well as features multiple model versions, scenarios, and time periods.

Based on the actionable insights provided by the platform, businesses are capable of:

  • Identifying the least/most profitable customers
  • Determining the net profitability of stock keeping units, customers, and suppliers via
  • allocation of indirect costs and value-added services
  • Addressing bottlenecks and removing non-value added costs
  • Estimating the profitability of potential contracts

To ensure efficient analysis, our developers represented the aggregated data as OLAP cubes. This allowed for driving meaningful insights from massive arrays of unstructured data.

Team

  • 1 project manager 
  • 2 backend developers
  • 1 frontend developer
  • 1 QA engineer

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    Founder