Transforming Compensation Forecasting for Experian with Idea House Collective
CLIENT
Experian
DATE
April 15, 2023
Experian provides comprehensive data and analytics solutions to empower informed business decisions.
Measured Impact
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200x Forecasting Efficiency
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Decreased the amount of databases from 8 to 1
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Forecast time dropped by 75% with 90% less labor

1) The Company

Client Name and Industry

Experian - Data Industry

Background

Experian is the largest credit company in the world, renowned for its extensive data capabilities and services. This global giant has achieved numerous milestones in the data industry, cementing its position as a market leader.

2) The Challenge

Initial Situation:

Before collaborating with Idea House Collective, Experian faced significant challenges in meeting its financial targets due to problematic compensation planning, particularly in the last month of each quarter.

Specific Problems:

The compensation models, which included substantial quarterly bonuses, lacked the necessary data for precise forecasting. This resulted in material impacts on earnings. The outdated compensation model failed to incorporate the required data, leading to inaccuracies in financial projections.

Goals:

Experian aimed to achieve more timely and accurate financial forecasts, minimizing the risks and discrepancies caused by the existing compensation planning issues.

Previous Attempts:

The company had previously attempted to refine the forecast accuracy by working with the sales team. However, this approach highlighted issues with sales reps’ goals and posed risks to the finance department, proving ineffective.

3) The Solution

Our Approach:

Idea House Collective began by thoroughly analyzing the existing process, identifying both its strengths and weaknesses. We collaborated with the IT team to explore available data feeds that could support a new, more efficient process. Following discussions with the finance team, we engaged the sales team for signoff and feedback. The new process aimed to automate forecasting, covering $40 million of variable compensation.

Systems Implemented:

The project was extensive, requiring collaboration across four functional groups. We developed a system that increased data requirements by 100x, enhancing accuracy through daily recalculations of projected bonuses. We also improved the accuracy of Salesforce data by implementing business rules that required data for compensation payments, thus eliminating "dark deals" from the process.

Services Provided:

We delivered consultancy services and built a new compensation planning system over nine months.

Collaboration:

Our team worked closely with Experian's sales and finance teams, forming a project team to provide feedback and validate data and compensation calculations. We held weekly progress meetings and monthly reviews with upper management to ensure alignment and transparency.

4) The Results

Key Performance Indicators (KPIs):

The success of the new system was measured by its ability to calculate, report, and validate variable compensation for over 200 sales representatives.

Quantitative Results:

Qualitative Results:

Client Feedback:

Experian expressed high satisfaction with the end product. While the sales team initially faced a learning curve, they quickly adapted, leading to a seamless and efficient process. The CRM became a single source of truth, and the sales team benefited from the daily forecasts to track their progress toward goals, especially in the crucial last days of each month and quarter.

Long-term Impact:

The new system provided Experian with a significantly more accurate forecast and better resource allocation to value-adding tasks, ensuring long-term efficiency and profitability.

This case study showcases Idea House Collective's capability to deliver transformative solutions that not only address immediate challenges but also provide lasting benefits. Through meticulous analysis, strategic collaboration, and innovative system implementation, we helped Experian achieve their goals and enhance their operational efficiency.

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