Financial Modeling & Forecasting

A Data Driven Approach to Leadership

One of the main obstacles for clinical executives and directors is the lack of decision-making tools and transparency needed to effectively lead. We focus on the following areas to improve your responsiveness to internal dynamics and the external healthcare environment.

Projecting Revenue

Develop and implement projections into your annual and quarterly budgets by using data related to patient volume, service mix and insurance claims among others.

Expense Forecasting

Accurately determine expenses and develop accurate projections needed to determine your operating income and cash flow to be used in the budgeting process.

Profitability Analysis

Understand your organizations profitability at the clinic, team, service and provider level. Develop data models that allow your leadership team to improve your service offerings.

KPI Development

Define the key metrics that drive the success of your organization and develop models that predict future outcomes based on those metrics.

Risk Management

Identify key risk factors that can impact the operational and financial performance and develop data models to monitor and mitigate those threats.

Machine Learning

Leverage large datasets to solve complex problems using statistical algorithms, neural networks and other AI driven methods.

Build your Data Model

Begin the process today and develop the decision tools you and your team need to make better decisions. Schedule a free consultation and create a plan for developing your forecast or data model.

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Modeling & Forecasting Process

We follow proven methods that allow leaders the flexibility to build the decision tools they need to succeed. Our process relies on agile development that provides transparency, flexibility and efficiency through the development process.

Determine Requirements

Develop a vision and use case for the data models and forecast your team needs to succeed. Plan and organize each feature into a series of sprints and establish a timeline for completion.

Establish Drivers of Success

Identify key metrics and data points that drive the data model and provide the most accurate forecast. Define and test each metric for use within the greater data infrastructure.

Leverage New and Existing Data

Collect and organize data into a automated workflows and develop data pipelines to move the data from it’s original source into the data model.

Implement Data Architecture and Models

Develop machine learning and advanced statistical models using defined metrics and requirements needed to complete each feature. Develop a data infrastructure that supports the data model and forecast.

Evaluate and Refine

Review the existing model and compare their output to actual results. Define ways to improve the current data infrastructure and model.

Outcomes

Higher Profitability

Leverage revenue projections and expense forecasting to determine current and future profitability.

Predictable Cash Flow

Develop models using metrics that improve your ability to monitor and manage revenue cycle management.

Transparency

Develop revenue cycle reporting from data models and forecasts to lead your organization and share results.

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