Employee onboarding: 5 things you need to measure if you want to improve

How you onboard employees is an absolutely critical component of the hospitality employee experience. 

The companies who get it right are able to get their new starters up to speed quickly and perhaps more importantly, they get new employees to fall in love with their brand.

But if you do it badly it can undermine the morale and performance of the whole team, customer service suffers and ultimately you churn too many new starters meaning that all that recruitment effort and cost just goes down the drain.

If you’re employing hundreds or thousands of people, it’s very difficult to improve your onboarding experience if you’re not measuring performance in a way that gives you real insight into what is and isn’t working.

So what should you be measuring in your new starter onboarding experience? Here are some suggestions to get you started…

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1. New starter satisfaction

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If your onboarding experience was a product, and your new starters were the users or customers of that product… how satisfied would they be with their purchase? Would they buy it again? Would they recommend it to others? 

We think you need to be collecting satisfaction data throughout a new starter’s first 90 days. 

What you’re trying to do with this data is to identify the peaks and troughs in the experience. What are the moments new starters appreciate and which experiences leave them feeling dissatisfied?

And you can use an automations platform like Youda to build and schedule these surveys so you can create a consistent, regular ‘pulse’ measure of what’s driving satisfaction.

Here are some examples of questions you could ask to gauge new starter satisfaction:
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• Satisfaction score at key milestones. It obviously depends on what your onboarding journey looks like, but there are likely to be some standout ‘moments that matter’ in the first 90 days. If you automate the scheduling and notification of these events, you can also use Youda to trigger automated feedback surveys so you can get an insight into how they went for the new starter. So you can ask questions like “How did your first day live up to your expectations?”; or “On a scale of 1-10 please can you rate how satisfied you were with the information pack we sent you before you started?”; or “How did your check-in conversation with [name of manager] go today?".
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• Employer Net Promoter Score (eNPS) e.g. “Based on your experience of working at [brand], how likely is it that you would recommend us to your friends and family as a place to work?”
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• Daily shift feedback. If you have a webhook on clock-in/clock-out, then you can use Youda to send someone a quick survey every time they finish a shift. Asking “How was your shift today?” with a 5 point emoticon scale would give you an insight into whether there’s an ‘emotional drop-off’ or lull in the first 90 days. If asking for feedback every day feels a bit much, you could try a weekly check-in instead.
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• Are you getting the basics right?  It’s easy to forget about those good old ‘hygiene factors’. There will be things that you might not want to focus on, but which matter a lot to a new starter. It’s worth asking about things like the uniform (Does it fit? Have you got enough t-shirts?), the training a new starter’s received, the support they got from a buddy, pay and benefits etc.
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Adding some AI magic sauce…

Automating your feedback loops makes a huge difference. It means you can start to build up a consistent and comprehensive perspective on the experience of new starters. But it’s now also possible to use AI to get a deeper insight into what’s driving satisfaction scores.

With our natural language processing capabilities, you could create a Youda chatbot to follow-up on questions and try to get a deeper insight. For example, you could set up a bot to monitor for an exceptional answer. So if a new starter says they’ve had an awful first day, the bot can jump in and ask follow-up questions to try and get a deeper insight. e.g. “Hey Freddy, really sorry to hear you had such a bad day. Can you tell me a bit more about it?”, “What went wrong?!”, “Have you got any suggestions or advice about how we could have done a better job?”. 

The chatbot agent can then send you a transcript of the conversation so you get an immediate flag and some insight into what’s going on. Giving you and your managers the chance to respond quickly and turn things around.

And over time, as you collect more of this type of natural language data, you use Youda’s analytics to identify themes and opportunities for improvement. So you could ask Youda: “What are the most common reasons people give when people have a bad first day?”.

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2. Speed to alignment

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In this context, what we mean by ‘alignment’ is the extent to which a new starter feels like they ‘belong’ at your company, that they’ve ‘settled in’ or are ‘at home’ as a fully bought in member of the team.

With speed to alignment data, you’re looking to identify how long it takes for a new starter to ‘get’ or ‘buy into’ your brand, values and culture. This matters because it ought to give you an insight into a new starter’s engagement and in turn, it should provide some predictive insight… all other things being equal, you’d expect people who don’t feel like they belong to be more likely to leave or to be employees who demonstrate ‘presentism’. And if you have pockets of disengagement or misalignment in a team that you don’t try and address, it’ll likely start to show up in the customer experience and business performance.

Examples of questions you could ask to get an insight into speed to alignment:

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• Do you feel like you ‘belong’ at [brand]?
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• Do you feel like you’ve made a good choice to join us?
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• Do you feel like you can be yourself at work?
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• Do you feel like you’re part of our team?
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• Are you proud to work at [brand]?
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3. Speed to effectiveness
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If speed to alignment is about giving you an insight into the subjective state of the new starter, speed to effectiveness is a bit more objective. It’s a measure of how long it takes for a new starter to become productive. 

This is obviously a really important marker to try and get on top of, because it means you can take a data led approach to improving your onboarding training. All other things being equal, the faster you get a new starter up to speed, the more value you create for the business. And marginal gains in speed to effectiveness can really add up when you’re operating at scale or doing lots of new openings. But it’s also an insight you can use to inform your recruitment strategies… if you know it takes x weeks for someone to become net productive, then you can add that cost to your cost of hire to calculate the payback period on a new hire. This is a really important calculation if you want to offer people short-term gigs or holiday work.

Examples of things you can measure to get an insight into speed to effectiveness:

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• Demonstration of key skills and behaviours. For the key roles in your business, you’ve probably already got a competency framework of the skills people need to do that job. As part of your onboarding journey, you obviously need to be assessing whether new staters can do these things and giving them training if they can’t. In our view, it’s in the interests of the business to make the acquisition of skills user-led (i.e. you should go as fast as the new starter wants) and to test different approaches to training these skills so you can work out what training works for who. Another thing we’ve seen work particularly well in a QSR business is to incentivise the acquisition of skills. The more stations a new starter could do, the higher their hourly pay. 
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• Is the new starter in the ‘Flow channel’? This is a blog in itself to be honest, but to try and keep it brief: flow is a concept developed by the positive psychologist Mihaly Csikszentmihalyi. His view is that the ‘flow state’ is the optimal human condition. If you’ve ever had an experience of losing track of time and being ‘in the zone’ when playing sport, music or at work… then you’ve experienced flow. We get into a flow state when our strengths are very slightly stretched by the task we’re working on. If the challenge of the task is too great we get stressed. If it’s too low, we get bored. And as we acquire skills over time, the challenge needs to increase to maintain our attention. Measuring flow (e.g How did you find your shift today?: very stressful - slightly stressful - just right - slightly boring - very boring) will give you an insight into a new starter’s subjective experience of the journey to effectiveness and ideally you want to keep people in that flow channel.
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4. 90 day turnover

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90 day turnover is one of the few standard benchmarks in the hospitality industry (and if you’re a UK-based hospitality company, you can sign up to Pineapple and get the benchmark).

It’s an easy one to understand and measure: how many new starters are still with you after 90 days?

Our advice is to structure your 90 day turnover reporting as a monthly cohort analysis. E.g. Of the people who started with you in January, how many had service of more than 90 days?

We’d also recommend asking all new starters “How long do you expect to stay with [brand]?” At some point between signing their contract and their first day. Why? Because in our opinion there’s a huge difference between an employee who joins you expecting to stay for 2 years, but who leaves after 2 months; and an employee who takes a summer job with you, has a great time and then leaves after 2 months to go off to university as planned.

Being able to report your 90 day turnover relative to the expectations of the employee really helps you identify where you have big issues, and it also means managers aren’t unnecessarily disincentivised from hiring employees on a short-term basis.

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5. Demographic and situational data

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This is where things can get really interesting: when you start to cross-reference the measures above (satisfaction, speed to alignment, speed to effectiveness and 90 day turnover) with the demographic and situational data you have on your people. 

So as part of your onboarding process it really helps if you’re capturing information on things like:

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• Their first language
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• Whether people have some form of neurodiversity
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• Whether people have a disability or chronic illness
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• Whether people have previous experience working in hospitality
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• DE&I data on things like gender, race etc
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• Whether people are studying outside of work
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• Whether employees have kids or other caring responsibilities 
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• How long it takes for people to commute into work
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And you should also be able to pull data from your rota to understand:

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• How many days holiday people took in their first 90 days
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• The shift pattern for new starters: whether they had two days off in a row; how busy their initial shifts were etc
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• The cohesion of the team around them… did they join a stable or unstable team
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What this data allows you to do is to start to segment your new starter population and identify the opportunities for improvement. You may find for example, that the biggest driver of 90 day turnover for full-time staff is whether people get 2 days off in a row. You might discover that not having English as a first language adds 2 weeks to a new starter’s speed to effectiveness. Or it might be that the data shows you’re doing a pretty good job for most new starters, but students working less than 8 hours a week are really dissatisfied, disengaged and churn at twice the rate.
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If you’re interested in getting this level of insight into what’s working, for whom, when and why… we should have chat, because that’s exactly the problem we’re looking to solve with Youda.