Why Your Data Isn't Delivering Impact

Hey everyone, it's Anthony Honesto and this is my latest drop for AI and HR today. Subscribe to the newsletter, the podcast, the YouTube channel. Just subscribe, folks. Do not miss a future article episode. Whatever. So what are we talking about today? We're talking about the challenges of AI in hr. There's few insights, generic strategies, and really no impact. Now, HR loves data. Yes, we're a data driven organization now and I love that piece of. And HR also loves AI, but where's the impact? There's too many disconnected tools, generic playbooks. There's no change. And you know what, folks? It's time to expect more from our tech products. Let's be honest, HR's obsession with data and AI has often become these days a paradox. People are now everywhere. Everyone is talking about data being gold, right? That's the new oil. And AI is being revolutionary. But sometimes many of us in HR look at these dashboards and they will overwhelm us. They, they don't enlighten us. And so what is the problem? Well, we're drowning in data. We get data, we're getting these charts and these graphs and all this data and all this over promising of, of. We're gonna, we're gonna give you data, we're gonna connect your systems over promise and very limited delivery. And we're starving for insights and that has to change. This is the HR data AI paradox. HR is no longer a support function. Folks, we're at the strategy table. We barged in the door, we grabbed our seat. No more talk of strategic hr. That assumes we were never strategic. I don't love that we're at the business table. We're, we're sitting in the boardrooms and we're ready and we're here to stay. But what we need to do, and the expectation of CEOs and boards is to translate data into action. Currently, we have a surplus of numbers and a deficit of meaning. Meaning the paradox isn't about throwing more technology at this problem, but the right solutions. We should no longer accept mediocrity and expect more from our HR tech tools. It is also not the only thing in terms of tool issues. We really need to transform our approach as a profession. Because if we don't evolve, we're going to remain in this loop of reports and data that impresses no one, frankly, and strategies that actually never materialize into business impact. So let's talk about the first element. Too much data. Let's call out the elephant in the room, the HRAS room. Too many systems, too many Formats and not enough insights, you're probably struggling. You have an HR system, you have a performance system, you have a recruiting system, you have all these different systems. They're disconnected tools, they're messy. There are manual processes still in each one of them. And what happens is it creates unreliable data. But when your insights are on this shaky ground, you're not making informed decisions, you're guessing. No more guessing game anymore. We need insights. We don't just need data, we need insights. And traditionally we've leaned into soft skills. So today many more HR teams are driving more data driven work. Like I've talked about before, because that's the expectation from the business. So if HR wants a drive strategy, we must continue to upskill, otherwise we risk not having a strong business impact. But the resistance is real. Change often feels threatening, especially when data challenges long term held beliefs. I love there's a live Data Technologies puts out some really interesting things on LinkedIn. And what they do is they take a headline and they look at the data behind the headline and often cross it out and provide real data. But transformation doesn't mean replacing human intuition, right? It means strength. How do we create alpha? It means that we have to strengthen it with evidence coming to the table with proof and insights. And we have to move past this fear and into this growth. Now the other element that has been challenging outside of too much data and no insights is generic strategies. Now you have this insight, which by the way took too long and involved too much data. How do you positively impact the actual problem? Maybe you look at a new HBR article. Maybe it's a framework you've read in a book somewhere. I'm saying this out of experience. I read HBR articles. I love radical candor frameworks, maybe even a program your network just suggested. You're in a bunch of these HR groups and emails and you ask for information from that source of data about potentially maybe driving great leadership. So the plan is now to introduce this strategy or framework to a group of leaders, not just one, but just because that's more efficient. So if you have a specific issue with a specific manager, yes, you can go to that manager and work with them on that. But what you often do is look for themes and start to train everyone at the same time. So instead of targeting the precise issue with the precise solution and strategy, you often do more generic strategies. I'm going to do 12 hours of leadership training across all of my leaders and we're going to train on all of these different elements and, and what you're doing essentially is like for that precise issue, you're just sort of over training folks and not hitting to that precise issue. So there's minimalized personalized coaching. Unless you subscribe to a third party coaching partner, which often requires several sessions, even if they're instructor led or human led, to really, truly get into the coaching, right? Cause what's happening is you're missing all this context. You don't have the context of the company, of the individual. What's happening then? The last piece and the challenge with AI, particularly in hr, is that there's no impact. So what happens in this train of. All right, I got my insight. I know what the problem is. I'm now training all my leaders over six sessions, over a whole quarter or a quarter and a half. Now you launch a training program for all these leaders, right? Not just those who will face some challenges. And you do it at a date that likely works for you or maybe your training partner, not necessarily the best date for your leaders. You conduct six sessions, they last two hours long. Again, see above, speaking from experience. And you do it over a full month. You conduct this likely via live or via zoom with a group of your managers. And really at the point, it's exciting because the participants in the session are prioritizing learning, right? They're showing up for the most part. But when you're in that session, you see them looking at their second screens. They're working on other things because the business doesn't stop, their work doesn't stop. I'm not blaming them because the work never stops. It's hard to really get their attention unless you bring them into a room, lock the door, and no laptops or phones allowed, which I'm not opposed to. But then you think about once you go through all this training and now maybe you're taking surveys, you're asking people about the training and getting their feedback. Do you have any clue whether the training actually created impact? Did your leaders actually operationalize that training, bring all those frameworks that you discussed into their daily operations? Frankly, there's no definitive way other than examining the same insight or the metric in the next quarter to see if anything you have done all that effort, all that mind shift and the training had made any difference whatsoever. So what are the key elements to get this right? Okay, Anthony. And I know you're asking, Anthony, what does this have to do with AI? Well, we need more insights first. There's just an abundance of data and there's just not enough insights. And if there are any insights and the company and its challenges. What happens is you're looking at all this data, you don't have enough insights. And the company and all its challenges continue to move forward. The company continues to struggle in whatever the issues are while you're looking at all this data and not having too many insights. Too many systems focus on bringing you data, bringing data to you, but none of the insights. You need intelligent insights that pinpoint precisely what is not working and by the way, what is working too. So you can be prescriptive about your approach to solving that. The programs you launch. So imagine looking at a dashboard and seeing every light is on. You're going to your car, you turn it on, every light is on. Like you're gonna panic, right? Everything seems wrong. That's HR tech today. You have no idea what the actual problem is or what challenge is happening within your organization. Then you need relevant strategies. Okay, let's say you have an idea of the challenge. The next step is to figure out what to do about it. And there are indeed a few systems that provide both insight and a selection of options on how to act. And it might be a framework in a new book like I talked about or an HBR article, but here you build personalized, relevant, impactful programs for those individuals. You know what the problem is, the precise problem, and then you target that precise problem with the relevant information and plan to attack that problem. And then what you do at the last part of this is you provide personalized coaching. Finally, you get through challenge number one. And number two, this is where the rubber meets the road, where you need to scale and operationalize the change. You need to make sure that your managers are bringing in this new framework, this new methodology, this plan, and hold them accountable. But how do you scale personalized coaching through your organization to tackle this exact problem directly with the leaders challenged by the exact issues that you talked about? Well, think about AI coaches, AI powered coaches that have both the context for the issue, the information about challenges, information about your business, information about your employees, and provide direction and advice directly in the everyday operations, in the leaders, slack or teams in their meetings, their messaging, their emails. What happens here is it builds the context. AI is so powerful when you have context. And then when you finally not only look at the precise issue, make the plan, hold people accountable, drive actions at scale. You need to understand, did any of this have an impact and an roi? So did that, you know, did you make an impact? Did that insight actually change positively? You really need to track these various indicators over time to ensure that what you're doing is having an effect. Think about whether it's performance. Do you have the right performance in your organization or could you allocate some of that human capital to other areas? And this is when your company is ready to invest. If you can show an roi, whether it's on a platform or your human capital programs or your people programs, absolutely will be easier. Discussions with your CEO and your CFO when budget time comes around. Now, AI isn't just the answer, but it will absolutely help. So when you're thinking about when we need to combine data from various sources, deliver personalized and detailed insights and strategies, and then develop plans to create an impact and ultimately integrate solutions into operations, that's where the real AI unlock happens. That's not AI jazz hands. And I'm just seeing that across HR tech these days. So when you have all of these elements, the context, all of this stuff in one system where the AI is helping you, then making the case for the return on investment for that program and that tool becomes super easy. It's my latest drop. Make sure you're asking these questions of your AI tools or your HR tools. What are the insights? How can I plan and act on those things? And how do I drive change at scale? Thanks for listening. We'll see you next time.