Turn Data into Better Decisions

Xb Analytics is a data science consulting company that
provides a variety of data analytics services.

The goal of Xb Analytics is to help you make better decisions by using data science to turn information into insights. My Services help add a quantitative element to any decision making process or may be used to evaluate past performance.

Let’s talk if you would like some assistance making sense out of your data.    



My name is Robson Glasscock, and I am the owner of Xb Analytics. I am a CPA with a PhD in Accounting from Virginia Commonwealth University.

I was an Audit and Assurance Senior Associate with KPMG before becoming a professor. During the doctoral program, I supplemented the required coursework with additional courses in econometrics, finance, mathematics, and mathematical statistics. My experience combines the financial reporting expertise of a CPA with the macro focus and quantitative tools of a PhD.

Previous clients have asked me to assist with financial forecasts, estimating damages for litigation, designing statistical sampling plans, and building an automated ETL system for oil and gas data. I specialize in creating clean, aggregated datasets from messy sources and then analyzing that data to provide valuable and actionable insights. 

Awards & Recognition

  • McGee, Hearne & Paiz Faculty Scholar of Accounting (2018)

  • College of Business Teaching Award (2018 and 2016) and Advisory Board Award for Faculty Excellence (2015)

  • J. Michael Cook Doctoral Consortium Fellow (2011)

  • KPMG Staff Leadership Council (2006)

  • KPMG Encore Award Recipient (2006 and 2005)


  • Microsoft Azure Data Scientist Associate

  • Microsoft Azure Data Fundamentals

  • Microsoft Azure Fundamentals

Please refer to my blog for examples of previous work. 
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Data Science
& Data Analytics

As a full-service data science consulting firm,  Xb Analytics will use data analytics to help you do what you do even better. Services range from data cleaning and aggregation all the way through to machine learning and include everything in between.


Litigation Support
& Expert Witness

Xb Analytics can help your legal team estimate the extent of damages or can take the stand to explain complex statistical or financial topics in a manner that the average juror will understand.

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Forensic Accounting
& Fraud Examination

If your organization suspects that fraud has been committed, Xb Analytics may be able to help you determine whether fraud has occurred, estimate the extent of the damages, and offer remediation advice to fix the internal control deficiencies that allowed the fraud to be perpetrated in the first place.


Education & Python Training

Topics include data science, machine learning, neural networks, anomaly detection, financial statement analysis, internal controls, risk assessment, and the application of data analytics to fraud investigations.

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Modern businesses have access to information generated from the tools and technologies they routinely use. Examples of internal sources include the customer relationship management system, human resources, accounting, vendor, and production data.  External sources include data about competitors, online customer reviews, and market trends.

The right information to answer the most relevant questions often exists in different systems throughout an organization. Datasets often need to be cleaned and combined before any meaningful insights are discovered.

Some organizations employ analysts who have the ability to use these various sources of information to aid managerial decision making while others do not.  I started Xb Analytics with the goal of helping small and medium sized businesses use the information they have to increase the effectiveness and efficiency of their operations.

Business owners and managers understand their businesses well. They know the right questions to ask but may not always have the capacity to utilize all of the organization’s data to optimize core operations.

My philosophy is to start by listening carefully to understand what management thinks drives optimal outcomes. The next steps are obtaining the data, choosing the appropriate data science techniques, and conducting the initial analyses. Results are then presented to management for discussion, exploration, and subsequent fine tuning of the analyses. The process concludes once management’s questions have been answered and clear a course of action is determined. 


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I enjoy using data analytics to provide insights, answers,
and alternative courses of action for decision makers.
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