Organization & Processes

Hannah Mayer. 7/2020. “AI in Enterprise: AI Product Management.” Edited by Jin H. Paik, Jenny Hoffman, and Steven Randazzo.Abstract

While there are dispersed resources to learn more about artificial intelligence, there remains a need to cultivate a community of practitioners for cyclical exposure and knowledge sharing of best practices in the enterprise. That is why Laboratory for Innovation Science at Harvard launched the AI in the Enterprise series, which exposes managers and executives to interesting applications of AI and the decisions behind developing such tools. 

Moderated by HBS Professor and co-author of Competing in the Age of AI, Karim R. Lakhani, the July virtual session featured Peter Skomoroch from DataWrangling and formerly at LinkedIn. Together, they discussed what differentiates AI product management from managing other tech products and how to adapt to the uncertainty in the AI product lifecycle.

Olivia S Jung, Fahima Begum, Andrea Dorbu, Sara J Singer, and Patricia Satterstrom. 7/17/2023. “Ideas from the Frontline: Improvement Opportunities in Federally Qualified Health Centers.” Journal of General Internal Medicine. Publisher's VersionAbstract

Background

Engaging frontline clinicians and staff in quality improvement is a promising bottom-up approach to transforming primary care practices. This may be especially true in federally qualified health centers (FQHCs) and similar safety-net settings where large-scale, top-down transformation efforts are often associated with declining worker morale and increasing burnout. Innovation contests, which decentralize problem-solving, can be used to involve frontline workers in idea generation and selection.

Objective

We aimed to describe the ideas that frontline clinicians and staff suggested via organizational innovation contests in a national sample of 54 FQHCs.

Interventions

Innovation contests solicited ideas for improving care from all frontline workers—regardless of professional expertise, job title, and organizational tenure and excluding those in senior management—and offered opportunities to vote on ideas.

Participants

A total of 1,417 frontline workers across all participating FQHCs generated 2,271 improvement opportunities.

Approaches

We performed a content analysis and organized the ideas into codes (e.g., standardization, workplace perks, new service, staff relationships, community development) and categories (e.g., operations, employees, patients).

Key Results

Ideas from frontline workers in participating FQHCs called attention to standardization (n = 386, 17%), staffing (n = 244, 11%), patient experience (n = 223, 10%), staff training (n = 145, 6%), workplace perks (n = 142, 6%), compensation (n = 101, 5%), new service (n = 92, 4%), management-staff relationships (n = 82, 4%), and others. Voting results suggested that staffing resources, standardization, and patient communication were key issues among workers.

Conclusions

Innovation contests generated numerous ideas for improvement from the frontline. It is likely that the issues described in this study have become even more salient today, as the COVID-19 pandemic has had devastating impacts on work environments and health/social needs of patients living in low-resourced communities. Continued work is needed to promote learning and information exchange about opportunities to improve and transform practices between policymakers, managers, and providers and staff at the frontlines.

Karim R. Lakhani, Yael Grushka-Cockayne, Jin H. Paik, and Steven Randazzo. 10/2021. “Customer-Centric Design with Artificial Intelligence: Commonwealth Bank”. Publisher's VersionAbstract
As Commonwealth Bank (CommBank) CEO Matt Comyn delivered the full financial year results in August 2021 over videoconference, it took less than two minutes for him to make his first mention of the organization's Customer Engagement Engine (CEE), the AI-driven customer experience platform. With full cross-channel integration, CEE operated using 450 machine learning models that learned from a total of 157 billion data points. Against the backdrop of a once-in-a century global pandemic, CEE had helped the Group deliver a strong financial performance while also supporting customers with assistance packages designed in response to the coronavirus outbreak. Six years earlier, in 2015, financial services were embarking on a transformation driven by the increased availability and standardization of data and artificial intelligence (AI). Speed, access and price, once key differentiators for attracting and retaining customers, had been commoditized by AI, and new differentiators such as customization and enhanced interactions were expected. Seeking to create value for customers through an efficient, data-driven practice, CommBank leveraged existing channels of operations. Angus Sullivan, Group Executive of Retail Banking, remarked, "How do we, over thousands of interactions, try and generate the same outcomes as from a really in-depth, one-to-one conversation?" The leadership team began to make key investments in data and infrastructure. While some headway had been made, newly appointed Chief Data and Analytics Officer, Andrew McMullan, was brought in to catalyze the process and progress of the leadership's vision for a new customer experience. Success would depend on continued drive from leadership, buy-in from frontline staff, and a reliable team of passionate and knowledgeable data professionals. How did Comyn and McMullan bring their vision to life: to deliver better outcomes through a new approach to customer-centricity? How did they overcome internal resistance, data sharing barriers, and requirements for technical capabilities?
2021 Feb 17

AI in Enterprise Series: Mohamed El-Geish (Cisco)

11:00am to 12:00pm


For Cisco, AI has become an appealing technology in customer service, specifically, in the customer contact center. Contact centers handle large volumes of inbound and outbound interactions, and make interaction channels (voice, email, text messaging, social media, etc.) as efficient and optimized as possible. In this session of AI in Enterprise,  Mohamed El-Geish (Director of AI, Cisco) discussed with moderator Doug Levin (Executive-in-Residence at Harvard Business School) the role of AI in customer experience, including speech recognition, natural language processing, virtual assistants, forecasting, computer vision, etc. and their applications in the enterprise.
 

You can also access the podcast or video recording through our Innovation Science Guide. 

 

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