Using Data-Driven Insights to Broadcast the Value of RPA and IA

Anshuman Das of WarnerMedia shares how he tracks & Quantifies intelligent automation success

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In the eyes of the business, quantifiable metrics make innovation real. Without tangible measurements in place to quantify the value of intelligent automation (AI) and robotic process automation (RPA), scaling these tools outside of IT is virtually impossible.

In order for business unit customers to not only adopt these tools but also leverage them in a way that maximizes ROI, they must first understand the value these tools bring to the table. Equipping customers with iteratively designed data analytics dashboards and data visualizations is a proven, powerful way of communicating how these tools impact the business and what can be done differently to optimize them further. 

Director and digital transformation leader Anshuman Das of WarnerMedia will join us this March 30-31 at the Scalable RPA & Intelligent Automation Live virtual event to share how his team uses data-driven insights to Broadcast Intelligent Automation Success Throughout The Organization. Walking us through the end-to-end implementation journey, he’ll shed light on how to measure and amplify the value of IA/RPA tools in a way that resonates with the business. 

The following are 4 key points he’ll be diving into.

 

Monitoring & Communicating the Value of Existing IA Applications

Tracking RPA & AI performance kills three birds with one stone: it enables you to ensure the tool is working as intended, illuminates next steps (i.e. expanding project scope) and helps customers better understand the value delivered by them. In addition, RPA bots and IA applications generate significant amounts of data-driven insights that, if properly harnessed, customers can use to enhance decision making. 

“As a technology professional, insights are extremely important because they not only satisfy customers by bringing value to them, but they also help us develop a future path for what we can achieve next,” Das told us. 

At WarnerMedia, Das’s team also collects data generated by the bots themselves and, using data visualization and advanced analytics techniques, packages it for customer use - a process that he will go through during his session at the Scalable RPA & IA Live

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Regression Analysis is Key to Cleansing and Consumerizing Data

Bad data in means bad data out, right? To ensure data is properly cleansed, findable and usable, Das relies on regression analysis modeling; a statistical process used to identify relationships between independent variables (predictors) and a dependent variable (outcome) within a dataset.

Once this framework is established, the next challenge is partnering with the customer to outline what types of data-driven insights they need and how to best deliver them. 

 

Data Visualization Speaks Louder than Spreadsheets 

Another frequently quoted adage is “pictures speak louder than words.” This is especially true when it comes to understanding and actioning data-driven insights. 

It is through data visualization that predictive insights truly come alive. In addition to being a powerful tool for communicating data-driven insights to non-technical business users, data visualization techniques enable WarnerMedia’s data scientists to experiment with and develop new, improved modeling techniques such as prescriptive analytics.

 

3 Pillars for IA Success

Throughout the RPA and IA lifecycle, Das recommends that you keep 3 things in mind: how you're doing business, how you're collecting data and what value you're bringing for your customers. 

 

To learn more about how RPA and IA generated insights can add value to your business as well as help enable wide-spread adoption of the tools, please reserve your “seat” at the Scalable RPA & Intelligent Automation Live virtual event taking place March 30-31, 2020. 

 

Scalable RPA & Intelligent Automation Live

The key for global corporate enterprise is to benefit from the collective intelligence presented by RPA and cognitive technologies along with human workers. Only by having technology combine with human talent can global corporate enterprise achieve scalable intelligent automation. And only with scalable intelligent automation enterprise resiliency be realized.

 

Join that community for lessons learned at SRIA Live.

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