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Brian Goodwin, PhD

Brian Goodwin, PhD

Contributions by Brian Goodwin, PhD

Data Science Primer: Reducing Downtime with Machine Learning

Downtime is one of the biggest financial risks in manufacturing. Asset-heavy companies are exposed to a lot of risk, because every time a machine breaks they lose labor costs, suffer from decreased production, and possibly even miss sales targets. But typical maintenance schedules are somewhat arbitrary and tend to be expensive. Companies pay technicians to look at machines in no danger of breaking down even as actual problems get overlooked. Machine learning allows manufacturers to combine sensor data with the power of the cloud to catch problems just before they happen, all while spending less on routine maintenance.
 

Brian Goodwin, PhD by Brian Goodwin, PhD

Data Science Primer: Clone Your Best Salesperson—Machine Learning in B2B Sales

When you use AI to help guide customer relationship management, machine learning helps you close more leads and optimize the revenue you’re getting from each one.
 
Whereas some AI projects are focused on reducing expenses—for example, by reducing manufacturing downtime—CRM-oriented AI projects are focused on expanding top-line revenue. CRM is a very strong fit for machine learning, because normally you have already gathered a lot of data on your market and your customer base.
 
If your company has been around for a while, you have data that describe past interactions. Information about the length of a sales relationship, the industry your client is in, the nature of the relationship, and the length of your typical sales cycle can all be leveraged into a predictive model. As a result, you can increase revenue and make more sales.
 

Brian Goodwin, PhD by Brian Goodwin, PhD

Data Science Primer: Predictive Analytics—How to Increase Profits Using Data You Already Have

Beyond Business Intelligence
 
Forward-thinking business leaders track KPIs and use tools like Power BI to create snapshots of what’s happening in the business from moment to moment.
 
Business intelligence is crucial because it helps leaders quantify their success and visualize relevant statistics in a meaningful way. But whereas business intelligence focuses on the present, predictive analytics looks toward the future.
 
At Concurrency we take companies beyond business intelligence by employing computational techniques to arrive at forecasts, or other predictions. Our methodologies carry a statistical rigor, which minimizes exposure to human intuition and helps you see correlations between seemingly unrelated parameters.
 

Brian Goodwin, PhD by Brian Goodwin, PhD

Data Science Primer: Sales Forecasting

Limits on humans’ abilities to take in vast amounts of data and make connections within the data set means conventional sales forecasting methods are limited in their accuracy and usefulness. Ultimately, a certain amount of human intuition is necessary—whether in what data to consider or what conclusions to draw from it.
 

Brian Goodwin, PhD by Brian Goodwin, PhD