S6 | 508: The self-optimizing enterprise with Don Schuerman, CTO at Pega
About the Episode
There is no question that greater reliance on predictive analytics, enhanced automation, and the capabilities of generative AI are helping to shape the enterprise of tomorrow.
Today we’re going to talk about building the self-optimizing enterprise, and how data, collaboration, and workflow optimization work together to create an organization where human creativity and innovation work seamlessly with artificial intelligence.
To help me discuss this topic, I’d like to welcome Don Schuerman, CTO & VP of Product Strategy & Marketing at Pega.
About Don Schuerman
Don Schuerman is CTO and Vice President of Marketing and Technology Strategy at Pegasystems, responsible for Pega’s industry-leading low-code platform for AI-powered decisioning and workflow automation. He has over 20 years of experience delivering enterprise software solutions for Fortune 500 organizations, with a focus on digital transformation, mobility, analytics, business process management, cloud and CRM. Don has led enterprise software implementations and provided technology and architecture consulting to senior business and technology executives from Fortune 500 organizations, including American Express, Citibank, JP Morgan Chase, and BP. Don holds a BS in Physics and Philosophy from Boston College.
Resources
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Synopsis
The podcast episode discussed the concept of the autonomous enterprise, which is a journey towards continuous real-time optimization using AI to drive agility autonomously. Organizations transition from manual and unmanaged processes to structured workflows, then to automated processes, and finally add intelligence to become truly autonomous.
An autonomous enterprise is an organization that constantly learns from customer interactions and workflow completions to enhance efficiency, effectiveness, and customer satisfaction. By leveraging AI technologies like generative AI, predictive analytics, and large language models, businesses can make data-driven decisions in real-time, resulting in improved outcomes and customer experiences.
To measure success in becoming an autonomous enterprise, organizations should focus on key performance indicators (KPIs) related to customer satisfaction, revenue growth, and operational efficiency. By monitoring progress towards autonomy, businesses can ensure continuous improvement to meet evolving customer and market needs.
Leaders play a vital role in driving the transformation towards an autonomous enterprise by fostering a culture of continuous improvement and embracing real-time optimization. By encouraging the use of AI tools, leaders empower employees to make data-driven decisions, focusing on creativity, innovation, and human-centric tasks while AI handles repetitive and analytical tasks.
In conclusion, the journey towards an autonomous enterprise involves cultural and technological shifts, where organizations optimize themselves in real-time using AI to drive agility autonomously. By embracing this journey and empowering employees to work alongside AI tools, businesses can deliver exceptional customer experiences, stay ahead of the curve, and achieve sustainable growth in today's dynamic business landscape.
Organizations should measure success based on customer experiences, business efficiency, and the impact on revenues and customer satisfaction. In the podcast episode, Don Schuerman, CTO and VP of Product Strategy and Marketing at Pega, emphasized the importance of real-time enterprise optimization. He highlighted the significance of driving efficiency and delivering desired customer experiences, which ultimately reflect in revenues and customer satisfaction.
Shurman discussed the concept of the autonomous enterprise, where technology drives agility autonomously, allowing people to focus on creativity and innovation. He mentioned that the autonomous enterprise continuously optimizes itself, whether in customer interactions or workflow efficiency, leading to better outcomes for the business and customers.
To track progress towards becoming an autonomous enterprise, Schuerman suggested focusing on key performance indicators (KPIs) tied to customer experiences and business outcomes. By moving workflows from manual to autonomous, organizations can measure success by the efficiency gained, the quality of customer interactions, and the resulting impact on revenues and customer satisfaction.
Based on insights from the podcast episode, organizations should prioritize measuring success by evaluating the improvement in customer experiences, the efficiency of business processes, and the overall impact on revenues and customer satisfaction to progress towards becoming a self-optimizing and autonomous enterprise.
To progress towards an autonomous enterprise, leaders and employees should gain hands-on experience with AI tools and technologies to understand their application and benefits. In the podcast episode, Don Schuerman, CTO and VP of Product Strategy and Marketing at Pega, emphasized the importance of hands-on experience with AI tools like generative AI. He mentioned that about 50% of respondents on LinkedIn had no access to such tools, highlighting a potential gap in understanding and utilization of AI technologies within organizations.
Schuerman suggested that the most important step for individuals and organizations is to actually use these AI tools. By engaging with secure tools provided by enterprises or exploring platforms like Pega's Gen AI Blueprint, individuals can gain firsthand knowledge and experience with AI technologies. This direct interaction allows leaders and employees to understand the capabilities of AI, how it can be applied to business processes, and the potential benefits it can bring to the organization.
By actively using AI tools, individuals can familiarize themselves with the technology, its functionalities, and its limitations. This hands-on experience enables them to explore the possibilities of AI in optimizing workflows, enhancing customer interactions, and driving efficiency within the organization. Additionally, gaining practical experience with AI tools can help leaders and employees identify opportunities for automation, data-driven decision-making, and continuous improvement in real-time.
Overall, the recommendation to gain hands-on experience with AI tools aligns with the idea that understanding and utilizing these technologies is essential for organizations to progress towards autonomy. By actively engaging with AI tools, leaders and employees can unlock the full potential of these technologies and drive the organization towards becoming a self-optimizing enterprise.
Don Schuerman, CTO & Vice President of Marketing and Technology Strategy, Pegasystems
