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Read time: ~ minutes

Hey Reader 👋🏻

Ok, here we go with Part 2 of this mini-series on People Product Performance Metrics 👀

If you are new to the newsletter, check-out part 1_, then pop back here to read on 🤘🏻

In part 1 I speculated that "part 2 will bring some validation, some challenge, and some new metrics to consider" - turns out my prediction was bang on. My additional research revealed that I am on the right track. Not overly surprising as I am drawing on my own lived experience as a product-minded Head of People, as well as on direct inspiration from what works in Product and GTM - but still, it's always nice when research validates your thinking!

Although to be clear, validation wasn't my intention - I would have been happy to be proven wrong if that led to be me finding a better approach to share.

With that said, I am holding firm with my 3 categories of People Product Performance Metrics for now as they seem to map pretty well with the approach others are taking give or take some semantic and optic differences / preferences.

A reminder, those categories again are:

1️⃣PX Product Health

2️⃣People Product Team Performance

3️⃣Initiative-Level Impact

This was by no-means a study of huge depth, but I have tried to source from multiple sources to give me a little bit of rigour:

• A selection of contributions from LinkedIn engagements
• (light) survey responses from some in-role PX Product Leaders
• An extensive chat with ChatGPT on the subject
• A selection of blogs and articles from some brilliant thinkers and builders in PX

I want to give some shoutouts to people who contributed directly or indirectly to my research:

🙏🏻 Vitor Cintra - Product Ops Manager @ Nubank, Kyle Ireland - Head of DEI & PX @ Axiom, Tal Hadas - VP of Engineering / CTO @ Veratrak, Camilla Miehs - CPO/VP People turned Advisor & Consultant, Norman Law - Director of Talent Technology and Portfolio Management @ Netflix, Adam Axon - Founder @ Give A Dam (former People Director), and special mention to Jessica Zwaan for the immense body of work she has produced on ELTV and People Ops performance metrics 🙏🏻

Ok, let's get into it...

Before I revisit my refined performance categories, I want to make two points on data use which came up time and time again in a variety of ways in the research.

1️⃣The goal is to be data-informed, not data-led.

Jessica Zwaan references, Goodhart's Law in one of her articles on the subject of data use in People Ops. The law states; "When a measure becomes a target, it ceases to be a good measure."

Don’t create outcome metrics as goals then orient your efforts to delivering them. Instead, establish baselines for important data-points (the things that actually impact people and business performance), then experiment and build intentionally to improve them (whilst looking out for emergent opportunities for value creation revealed by the data).

This might be controversial to say, but I genuinely believe it: it's better to measure nothing, than to measure everything.

Much better to have fewer data-points which are relevant and useable than having a fancy dashboard of “stuff” - things that look nice in a graph but mean sweet f*ck all when it comes to making strategic data-informed decisions.

A lot of the data we have access to in HR falls into the later category. Lot's of it. Very little useable insight. It also often leads to paralysis by analysis - it can feel impossible to make a decision when you are overwhelmed with data.

A decision made on intuition is more valuable that a decision not made with data.

2️⃣Data is useless without context

Data without context is just noise. You can report on participation rates, completion stats, or engagement scores all day long - but without understanding why people are behaving a certain way, what matters to them, and what else is going on around them, those numbers are meaningless. Context turns data into insight - and insight is what drives good decisions. Good decisions lead to value creation.

As I said last week, We are not short of data in People Ops... The challenge is making that data relevant and usable, crucially it's about not just measuring activity and observation, but measuring impact and insight. Impact and insight can only come from data in context.

👀Performance Categories (revisited)

Ok, how has this all informed my thinking relative to my defined categories?

Rather than setting out the full set of specific metrics under each category (I will do that in part 3 of the series - along with a usable template for you to steal and use) - I want to add a little more depth to the structure, hierarchy and application of the categories informed by my research. I have listed them in order of priority.

🚑PX Product Health

PX Product Health is the most important category to establish as a top priority for all People functions, whether you are "product-led" or more traditional in your approach, if you want to show the correlation between the work delivered by the People function and business performance, this is a fundamental category to establish.

I also think it can be relatively simple - remember, it's better to have fewer data-points which are relevant and useable than a big dashboard of “data” which is out of context and non-specific.

What's being measured:

• Value - created for the business and employees (ELTV)
• Impact - the People initiatives delivered support core business objectives (Org specific)
• Retention - compounding value creation (MRV / ARV - Monthly/Annual Recurring Value)

You could group these under the banner of; Growth.

I will add specific metrics and definitions under each in Part 3. Essentially, the PX health metrics form a kind of “north star collection” of key indicators which show that the People product is performing well (delivering business growth), the PX value prop is strong (employees are performing and want to stay), and the People Team is aligned strategically with core business objectives (People workflow has a positive correlation with top org priorities).

These are the metrics you take to “the table” which irrefutably show that the work being delivered by the People Team is contributing to revenue growth, business performance and organisational health - getting clear with your PX Product Health metrics will allow you to really show the value and impact of your work (with confidence). You will be able link specific programmes delivered to specific growth indicators.

Ultimately, If the PX Product is healthy, it’s HIGHLY likely that the overall business is healthy (and resilient).

🎯People (Product) Team Effectiveness

Second priority (and greatest area for operational improvement) is People Product Team Effectiveness - you can drop the "product" if you (or the business) aren't quite ready to go all in on the product-led PX concept, but you can still use this as a framework to measure the right things to assess People Team effectiveness.

What's being measured:

• Velocity - how much work is delivered/value is created per sprint/period of work (quantity)
• Cadence - rhythm and regularity of work being delivered (frequency & consistency)
• Quality - how well solutions/programmes meet end user needs (usability & satisfaction)

These are the top line categories of execution effectiveness. Under each you would have a series of measures categorised by core function or work stream, I will suggest some in Part 3. These would vary depending on team size and structure - if you are stand-alone you will need to be across all of these work streams, but remember to prioritise the stream of maximum impact to current org objectives and priorities.

If I was building a People Product Team right now, this is how I would structure the function:

• People Ops (core People OS - compliance, technology, processes, efficiency, scalability)
• People Product (core PX - engagement, feature & programme development, experimentation, growth & retention)
• People / Talent Acquisition (GTM - awareness, attraction, conversion)
• People Partnering (activation & success - business partnering, employee support, manager support)

Even in a stand-alone role, I would be structuring the function like this and splitting out my objectives, tasks and priorities under these categories as workstreams. You would just need to prioritise execution under each category based on business needs. I would also say that establishing a solid People Ops foundation should ALWAYS be first-priority. This should not be compromised. Check out JooBee's Inverted HR Hierarchy of needs as reference for why solid People Ops is critical if you want to move on to deliver more value creating work.

💥Initiative-Level Impact - conversion, engagement, utilisation, and Return-on-Effort (ROE)

This is the 3rd level of performance tracking, and possibly the one which may feel most alien to HR teams. However, whilst this is the final layer of rigour to add, for me it is the layer that offers the greatest opportunity to deliver exponential value. As well as allowing you to understand how well an initiative performs, at this level you are also getting into the exciting zone of "growth-hacking" - identifying the opportunities and experiments that could deliver the 10x improvements.

What's being measured:

• Conversion - % of employees who use or opt-in to a PX feature, programme, or initiative
• Engagement - the frequency and meaningfulness of employee use of a PX feature, programme, or initiative
• Utilisation - % of total eligible users who are actively using a PX feature, programme, or initiative
• Return-on-Effort (ROE): Ratio of effort to measurable value created by a PX feature, programme, or initiative

Each of these categories would have multiple measures which allow you to assess relative performance of an initiative against each - again, I will offer some recommended measures for each in the final edition of the series (I did offer a handful in lasts week edition).

Ultimately, you should aim to get to the stage where you have impact tracking in place for all initiatives delivered, features and programmes shipped. These metrics tell you at the granular level which programmes are delivering the most value, which have missed the mark, and in both cases, where are the greatest opportunities for improvement.

I hope this has provided a little more clarity and rigour to my suggested structure and framework for performance tracking for People Teams. In part 3 I will close out the series with my full suite of recommended metrics for all categories outlined, along with a usable template which you can pick up and adapt for your culture and context.

OK, that’s a wrap for this week.

Part 3 will follow next week (or the following week) depending on how I get on with the template build 😱

Either way, grab your coffee and open up your inbox same time next week for more insights, tips, and resource flags on how to smash HR silos, add strategic value and turn your People function into a growth driver 🚀

With love,

Luke ✌🏻

PS, when you are ready you might like...

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