3 Tips for Utilizing Data Analytics to Drive Your Business Forward

Changes in data analytics are helping businesses make smarter choices for their future.

Predictive data analytics in the business world is becoming more and more necessary as it develops. Companies that do not adapt to the changes that predictive analytics brings forth will soon find themselves left behind on the road to success.

Here are three ways you can use ‘Big Data’ to help drive your business towards better outcomes.

1 – Focus on Data Agility

This means that the data software being used has the ability to understand data contextually as it arrives and the ability to take appropriate action concerning that data. The capability to both collect data and know how to use it to the best advantage can give a company the competitive edge in the marketplace, as well as building a pool of information that can be used anytime.

At TSI, we understand how important it is to be agile. Quickly understanding the characteristics of each account placed with TSI is crucial to implementing the correct collection strategy for our clients. Efficient data storage and processing allows for raw data to be converted to informative features within a matter of minutes when account enters our data warehouse. This allows for predictive analytics to correctly assign the actions needed to collect on an account-by-account basis.

2 – Utilize Real-Time and Dynamic Analysis

Although historical data is still useful to build the models that provide the basis to anticipate future actions needed, advances in technology allow businesses to employ pre-emptive and dynamic analytics that actually drive transactions rather than follow them. In addition, real-time observations and adjustments allow businesses to swiftly change their approach or take advantage of a new opportunity. These new analytics tactics not only allow a company to recognize new streams of revenue and save costs, but they can also drastically improve customer relations, through improved service.

TSI’s robust data storage architecture is designed to allow for efficient computation and processing. This provides our data scientists and business intelligence analysts the ability to develop and monitor statistical models and the KPIs used to continuously improve our services for our customers. Model/concept drift and other statistical properties affected by a changing and growing population of data can be accounted for, keeping models and algorithms operating effectively. By being able to monitor our actions and strategy using real-time data, we maximize our chances of success.

3 – Don’t Get Left Behind

Companies that continue to manage their data in separate ‘silos’ from the rest of the business are quickly headed towards being obsolete. A business that can’t accurately forecast market shifts or predict customer behaviors ahead of time will soon be phased out of the market. Throughout history, industry leaders are the quickest to adopt new, effective tools for improving their business strategies.

The data science and business intelligence teams at TSI are constantly looking at ways to improve our predictive analytics strategy using the latest tools and methods. From developing and testing new machine learning methods using SAS & Python, to creating dynamic report dashboards in Tableau, each improvement has resulted in increased recovery for our customers.

Analytics in Collections

Collections companies that ‘aim for the big fish’ with the goal to collect on bigger debts first and then move on to smaller debts, may not have the best approach anymore. This old-school method of collecting on outstanding accounts is quickly shifting to a predictive and data-based outlook that is drastically improving results.

Smart analysis tools can now help collection companies streamline their strategies using an ever-growing base of data points. Utilizing multiple datasets across platforms reveals a more comprehensive picture of specific accounts, allowing collection companies to better prioritize targets and generate more accurate recovery scores.

At TSI, we utilize a proprietary data analytics platform called CollectX. This smart framework allows you to pool your customer data resources and realize benefits like improved call-through rates, higher conversions and right-party contacts, and faster recoveries. And, because CollectX scores accounts on collectability, TSI reduces compliance risk and the opportunity for massive fines by ensuring repeated attempts to contact consumers unable to pay do not occur.

TSI takes predictive data analytics to a whole new level within the collection industry. To see how our proprietary platform CollectX can start driving better recovery outcomes for your business, contact us today.

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