PlanYear AI Newsletter - June 2024

PlanYear AI Newsletter-1

Welcome to the PlanYear AI Newsletter for June 2024! The goal: to help you understand artificial intelligence within the context of employee benefits.  Each issue, we’ll provide articles, case studies, and insights about what's going on in AI for Employee Benefits (EB).

Artificial Intelligence is becoming increasingly central in societal discussions. With Apple planning to integrate AI into nearly every aspect of their product lines, and both OpenAI and Google unveiling new large language models (LLMs) in April, the pace of innovation only feels like it’s continuing to accelerate.

Given the challenging macroeconomic environment over the last few years, it seems appropriate to focus this month’s newsletter on AI's impact on EBITDA or Earnings Before Interest, Taxes, Depreciation, and Amortization (a company’s overall financial performance). We’ll explore how AI is positively impacting profitability across industries, and draw parallels to Employee Benefits specifically.

How are teams using new technology, and what impact is it having on their profits?

In the realm of employee benefits, AI is freeing brokers and benefits consultants from traditionally manual data workflows. Teams no longer need to spend hours transforming data from the carriers into a usable format. Firms who adopt AI into their workflows now will experience a compounded impact on their bottom line heading into future renewal cycles.The impact of this shift is potentially massive.

The Impact AI is already having on Operating Costs across Industries

It's no secret that Generative AI is rapidly changing how business is done. Even though AI technology is still relatively new, industries that are investing in AI have already seen a substantial impact to their bottom line. 

Here is a quick breakdown on how industries across the board are capitalizing on these efficiency gains: 

In healthcare, hospitals are using AI to predict patient illnesses by analyzing vast amounts of patient data. This allows staff to take action before conditions worsen, reducing the need for long hospital stays and saving both money and resources. For example, Johns Hopkins Hospital implemented a command center using predictive analytics to manage patient flow. Within this command center, algorithms notify staff of the highest impact actions they can take to reduce wait times such as room turn or patient discharge. In addition, automated alerts have been implemented if staffing levels fall to inadequate levels This system results in a 60% improvement in admitting patients with complex medical conditions, 30% faster bed assignments in the emergency department, and a 21% increase in patient discharges before noon. By using AI, hospitals like Johns Hopkins are improving patient care and operational efficiency.

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In manufacturing, BCG, a global management consulting firm that advises businesses in the space, unveiled an Advanced Production Scheduling (APS) tool to help plan manufacturing projects. Instead of planners spending hours manually organizing work schedules, the AI model analyzes data to find the best schedule in a fraction of the time. This technology shift has improved Overall Equipment Effectiveness (OEE) by “over 3%, and cut the hours spent on planning by more than half.” As a result, factories can produce more products faster and save money on labor costs.

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The telecommunications industry is also experiencing significant EBITDA impact in 2024. Microsoft recently commissioned a study which showed that “for every United States dollar that a telecom company invests in AI, it realizes an average return of USD 3.50.” AI is not just profitable however, it is also hugely popular among employees. According to their special Work Trend Index report, 77% of users of Microsoft Copilot, an AI tool for telecom teams, didn't want to give up the tool due to how much time it saved.

Source - https://www.microsoft.com/en-us/industry/blog/telecommunications/2024/01/03/generative-ai-provides-a-big-boost-to-the-telecommunications-industry/

What parallels can we draw to Employee Benefits specifically?

Like the examples above, the benefits industry is moving away from a time when manual tasks took hours and potentially days to complete. 

For example, with PlanYear, firms can ingest carrier data with AI instead of spending time and resources updating spreadsheets. AI's ability to ingest data allows brokers to work more efficiently with clients. Brokers can create proposals in seconds, share them with clients, and collaborate on iterations in real time so that they can get to final decisions faster.

One of the goals of technology should be to maximize the time spent building relationships with employer groups.

In the brokerage industry, we observed that finding account managers proficient in both interpersonal skills and analytical knowledge is rare. If account managers could leverage a user-friendly platform that did not require any quantitative skill or Excel expertise to create proposals, hiring would be much easier. Similar to how telecom employees use Microsoft Copilot to efficiently process and analyze large volumes of customer data, identify network issues, and predict maintenance needs, solutions like PlanYear enable account managers to handle historically complex modeling scenarios without needing to understand intricate formulas. By simplifying data analysis and automating routine tasks, these tools reduce the complexity of managing clients, allowing account managers to focus on long term strategy and client relationships.

What this means is that firms can strategically hire for exceptional interpersonal skills, allowing them to manage increased workloads more efficiently during peak renewal periods. By optimizing staffing, firms can scale their operations without a significant increase in hiring. Just as in the healthcare industry, proper staffing in employee benefits directly impacts a business’s bottom line. Ensuring the right people are in place during busy seasons helps maintain service quality and efficiency, ultimately boosting profitability.

Staffing is just one example. Another problem we often hear when speaking with benefits brokerage is that they don’t have a sense for how to quantify ROI per dollar spent on technology. Piecing together a stack of quoting tools, AMS systems, decisioning support, and employee communication solutions (or some other combination of these) can be costly. Paying for a tool when you still need to manually transfer the data to another piece of the renewal cycle doesn’t make a ton of sense. 

Firms that make embracing AI a priority can significantly enhance their service speed and efficiency, leading to a competitive advantage in the market. By adopting AI, brokers can transform their operations and deliver real-time, data-driven insights, ultimately driving better outcomes for their clients. 

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In conclusion - AI is here. Its impacting EBITDA across all industries. In fact, according to Mckinsey, Generative AI is “expected to contribute $2.6 to $4.4 trillion to the global economy annually.” Enhancing customer operations, marketing, sales, software engineering, and R&D all contribute to these gains. Taking clues from other industries, and finding the parallels necessary in benefits, may be helpful in order to prioritize strategy. So far, considering the impact across industries and the speed AI continues to move, it's looking like a good bet.

Source - https://www.mckinsey.com/industries/financial-services/our-insights/insurance-2030-the-impact-of-ai-on-the-future-of-insurance

Thanks for reading - and stay tuned for the next issue of the PlanYear AI Newsletter! 

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