Topic: CYBERSECURITY & TECHNOLOGY

Today, any business that doesn’t capitalize on data advancements risks being swept away with the tide. PEOs in particular should think of data as a direct pipeline to the resources you and your clients need to navigate the complex world of HR and compliance, and make better business decisions in the process.  

AI holds the potential to revolutionize the insurance and benefits industry, contributing to risk reduction, enhanced customer service, and augmented efficiency. The potential of automation and generative AI is boundless, and adoption continues to surge.

We’ve now reached a critical juncture where companies need to make a few important decisions about how to use AI. Many topics will include both HR and HCM, meaning countless companies will be looking to their PEO partners to provide guidance in navigating the increasingly complicated AI waters.

The pressing question for organizational leaders centers around how to leverage data strategically and productively toward meaningful results. Here is a simple framework to drive value and impact through the use of quality data.

I have often found myself standing for minutes in my nearby Publix trying to figure out which item to buy. Did I want the $2 name brand product, or the $1.50 Publix generic version? Did I want the less tasty Gala apples at $1/lb or the tastier Honeycrisp apples at $2/lb? I would stand there paralyzed by the decision.
 

Thankfully, at some point, stomach pain kicks in and forces you to make a decision. But in real life, there are many in PEO leadership who are staring blankly, maybe even petrified and anxious, in the aisle of predictive models trying to figure out how to decide between different companies. So, let me do my best to present you with points you should consider to move from trepidation to triumph.
 

First, two caveats. The first one is that this is not comprehensive. Writing a thorough treatise on this would take too long and I’ve already used enough of my word limit. The second caveat is that this article is focused on analytics firms providing underwriting, pricing, loss control, or claims-level solutions that are commonly marketed as AI.
 

So, how does one select an AI vendor in claims, loss control, underwriting, or pricing? 

CONSIDER THE BUILD VS BUY DECISION 

There are a lot of considerations going into this decision, but it’s worth checking this point off before you start heading to the analytics store. Building something in-house or even with outside support could be a better option if you’re looking for a more customized solution, have in-house technical expertise and resources, and/or need a quicker turnaround. The customization aspect is important because PEOs are not insurance companies, and so you’ll want to find a vendor that can not only spell P-E-O, but also know how a model implemented with you would differ from an insurance carrier. 
 

It is worth noting that I have definitely seen companies start off with great intentions and then end up with more money spent and less of a product than if they had just outsourced the work from the get-go. Going with an external vendor can mean avoiding diverting too much attention and resource from other parts of the business, having immediate access to specialized expertise, proven technology, and on-going support.
 

HAVE THE RIGHT PEOPLE LEADING THE RFP 

A request for proposal (RFP) process or something akin to it is absolutely crucial to ensuring a methodical approach to evaluating the potential vendors. Internal stakeholders with previous experience are the most ideal, and it’s important to also incorporate other stakeholders if not into the actual process then at least to get feedback at the outset.  

Experience is key but a characteristic not to be overlooked is independence. Whomever you have leading the process, make sure that that person or group of people have the best interests of the company at heart, with no selfish motivations apparent that might impair their judgment.
 

LOOK UNDER THE HOOD 

It’s important that you, or the people you trust, understand the model design and how it compares against competition. I’ve seen models promoted as being robust and cutting edge, but once you get through an NDA and delve into the model details the model is shockingly dated and not well suited for anyone’s needs.
 

It’s also good to give it a test drive. How does the model perform on your own data? Having real-life examples can help you get comfortable with important details like the potential range of ROI and what a model “error” or incorrect prediction might mean financially and operationally.
 

DIFFERENTIATE BETWEEN SALESPEOPLE AND POST-SALE SUPPORT 

As you go through the RFP process, some firms will connect you with smooth-talking salespeople and flashy decks persuading you that your hard-earned budget will generate an immense return. However, after you sign the contract, you quickly realize and regret that the immediate attention you received from that salesperson is now replaced with inattentive and rigid interactions with the people actually doing the work. As you go through the RFP process, make sure you differentiate those two groups, and talk to the actual people behind the scenes.
 

A subpoint to this is understanding how important of a client you are for the company. Are you a smaller or larger client for them? Will they be willing to work with you on changes in the model because you’re a valued client, or will they brush you off because you’re booked as a win on last month’s sales quota?
 

PUSH FOR PERFORMANCE-BASED CONTRACT TERMS 

It’s great when companies say they want to share in your success and ensure there will be little downside to spending your budget with them, but what if they were able to codify those assertions in a contract? Having a contract designed such that you pay little when there’s little to no results, and you pay more when you’re swimming in ROI is a true partnership. Of course, the devil is in the details. You have to not only define “success” but be able to objectively quantify and monitor it over time.  

While there are many other considerations at play and each situation is different depending on the PEO’s history, sophistication, needs, goals, etc., the above points hopefully will help reduce some anxiety when looking at the different options in the predictive modeling aisle.  

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Cybersecurity is an essential aspect of business operations, which is why it cannot be viewed as the sole responsibility of the IT department. Cybersecurity threats evolve daily and organizations can best prepare and protect themselves by taking a shared responsibility to protect the company’s assets and data.

Every business faces different challenges whether from competitors, market changes, supply chain disruptions, or myriad external or internal forces. Yet every business, regardless of size or industry, faces a common threat: the security of critical data. Whether it’s the leak of proprietary business information or customer data, or a breach, or a malicious software attack, it can be devastating. Security incidents result in disruption, fines and a loss in customer confidence that can take years to recover.   

We all have locks and alarms on our homes, businesses, and vehicles. None of us would think about leaving our property unguarded. Why would you take the chance with your digital property?  So, what can PEOs do internally to help secure the vulnerable areas of their business? As IT Manager at ESI, I have the task of guarding the gates of ESI through various techniques. Hopefully, by sharing some of these techniques, we will add some nuggets to your cybersecurity protocol.  

The exposure of being an employer is dynamic and untenable for a small employer, which is why PEOs are so crucial to businesses. While core PEO responsibilities such as payroll, procurement of workers’ compensation, and human resources are foundational value propositions to assist employers, in addition to these areas what makes one PEO more attractive than another in the selection process? What is the biggest problem to solve for your client company? Maybe it’s safety. Usually, the area where they lack the most understanding and support is in cyber defense. Every client of yours is a sitting duck for a hacker and you can help.