Navigating the complexities of Employee Experience programmes (EX): Insights from EX professionals

Last month I had the privilege of hosting a roundtable at Qualtrics with 25 brilliant minds on all things Employee Experience. We laughed, we cried, and we shared some real challenges of running an EX programme for large enterprises. Don’t worry if you missed it, below are the discussion points and lessons learned.

1. The Cadence Conundrum: First up is the big question – how often should we ask for feedback, and when? Too often, you’re at risk of survey fatigue. Too little, you struggle to keep up with sentiment and trends in a fast changing work environment. Regardless of industry (hospitality, pharmaceuticals, professional services, banks) it was unanimous: BALANCE is key and no one had quite nailed it, yet.

Solution: Survey fatigue, as it turns out, isn't driven by the sheer volume of surveys. The real issue is when no action is taken. We all know how frustrating it is to not be heard. The question then turned to ‘how quickly can we take action on feedback?’ with most agreeing it takes around six months. So, if you’re surveying twice a year, are you capturing everything you need? Not really. To address this, there seems to be a shift from 'point in time pulses' to feedback on ‘in the moment experiences’. These range from work anniversaries, returning from parental leave, changing roles etc. One financial services organisation has even mapped out 50 key experiences that their 85,000 employees may go through to gather in-moment feedback from them as it’s happening. Ultimately, by zeroing in on real-time feedback, we not only increase the validity of responses but also boost participation rates!

2. To democratize, or not to democratize data, that is the question: There seems to be a fork in the road between giving managers direct access to their data, or serving up a curated platter of insights and action. Do managers have time to be drilling down for insights? Will they hone in on the right things, or fixate over niche negative comments? The answers seemed to be industry dependent.?

Solution: It's less about playing data hide-and-seek and more about empowering the individual manager. When managers grasp their direct influence on engagement and its cascading effects on productivity, retention, revenue, and overarching company strategy, they're better positioned to take action, irrespective of whether they have raw data or processed insights. The caveat being hospitality and retail businesses needing quicker, simpler ways to distribute actions as looking at data takes their managers away from their customers.?

3. The AI Ethics Enigma: As with any shiny new toy, there's excitement about GenAI in EX. Unless you’re a bank (I learned) then it’s a tightly closed door. But, if you’re not a bank, you’ll still be questioning the ethics of letting AI juggle employee data and suggest actions. No one wants a scenario of "the robot made me do it!"?

Solution: AI offers great potential, especially in analyzing large volumes of data and picking out key themes. It could eventually act as an interactive, virtual coach, guiding managers through understanding their scores and how they compare to external benchmarks - think chatbot. Does this help with our democratization of data dilemma? Potentially. Also, GenAI can summarize open-text comments into topics in a fraction of the time of current technology. Ultimately, we can run EX programmes in harmony with AI if it’s transparently communicated with employees and any actions from its analysis are guided by human intuition.

4. The Qualitative Quandary: Quantitative data often takes center stage due to its scalability and ease of analysis. However, employees paint vivid pictures, display emotions and provide solid advice in open-text answers. Given the time, leaders can extract powerful stories from open-text answers. The depth and nuance in this feedback means some companies are even looking to replace the majority of their multiple-choice questions with open-text to get to the route of how employees feel. However, this poses the questions of how you categorise key themes quickly and who you give access to these comments?

Solution: We’ve already touched on a potential solution - enter GenAI to find the feedback needle in a haystack. If we can harness this ethically, ensuring consistency in its analysis and have a human filter over its suggested actions, we may be able to harness the power of large volumes of qualitative data to improve our businesses. In terms of distributing this data, it was pretty much a consensus that only senior leadership need to review open text comments to maximize confidentiality protection.?

To summarize, when navigating the challenges of running an EX programme, it’s clear a blend of human intuition and advanced technology is central to success. There’s no ‘one size fits all’ approach. We’re all on the journey to harnessing in-moment feedback, democratizing insights and providing AI-powered analysis.?It’s about innovation, iteration and experimentation to find what works for your business. It’s a rollercoaster ride, hopefully with more peaks than dips????

I’d love to hear your thoughts in the comments below! How are you navigating these challenges and building powerful EX programmes??

If this has sparked your interested and you’d like to join us at our next roundtable, please drop me a note at rdavies@qualtrics.com?