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GROWTH

Forecasting & Predictive

UNDERSTAND

U

Conduct Interviews & Review Data

NAVIGATE

N

Map the Future

IMPLEMENT

I

Unlock Revenue Faster

TRACK

T

Track Progress

YIELD

Iterate & Evolve

Y

Using the UNITY framework, let's explore a specific scenario that may keep you up at night...

Scenario

Your team lacks foresight. Maybe they are amazing, often crushing critical targets. Unfortunately, everything is a surprise and there's no clear way to predict future revenue which means investing in COGS is always a reactive exercise.

01

Conduct Interviews & Review Data

  • Assess available data sources, quality, and completeness for revenue-related data. Identify data gaps and areas for improvement. 

  • Align data analytics efforts with specific revenue-related business objectives, such as increasing sales, optimizing pricing, or expanding market reach. 

  • Establish data governance practices to ensure data accuracy, security, and compliance with relevant regulations. 

  • Role plays with data analytics and revenue teams to ensure effective use of technology, tools, and platforms available for data analysis.

02

Map the Future

  • Define clear objectives for revenue forecasting and predictive analytics, including accuracy targets, revenue growth goals, and timeline expectations. 

  • Develop a data analytics strategy that outlines the approach for data collection, analysis, modeling, and reporting. 

  • Create a plan to integrate data from various sources, ensuring a unified view of revenue-related data. 

  • Create a training program for effective understanding of data and roll-ups.

03

Unlock Revenue Faster

  • Collect and integrate data from relevant sources into a centralized data repository for analysis. 

  • Establish predictive models and algorithms to analyze historical data and generate revenue forecasts. 

  • Create data visualization dashboards and reports to communicate insights and forecasts to key stakeholders. 

  • Deploy a roll-up process focused on informed and accurate projections.

04

Track Progress

  • Define key performance indicators (KPIs) related to revenue forecasting accuracy, revenue growth, and data analytics efficiency. 

  • Continuously analyze data and models to monitor revenue trends, identify anomalies, and assess the accuracy of forecasts.

  • Regularly communicate insights and findings to key stakeholders and decision-makers. 

  • Evaluate the effectiveness of data analytics tools and technologies in supporting forecasting and predictive efforts.

05

Iterate & Evolve

  • Analyze data accuracy and roll-up performance to identify areas for improvement in forecasting accuracy. 

  • Develop an improvement plan based on data analysis and stakeholder feedback, outlining refinements to data analytics strategies, models, or data collection processes. 

  • Conduct regular working sessions to ensure consistent progress without the need for full-scale change. 

  • Foster a culture of continuous improvement in data analytics practices, seeking new data sources and advanced techniques to enhance predictive insights and decision-making.

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