team – Joe Blogs

Product management takeaways

I’ve just spent two days with two Jeffs (Gothelf and Patton). They ran a great product management course, and I wanted to quickly get down some of my personal takeaway points, while it’s fresh in my mind.

The term MVP has been wrecked

This rang true as one of my bugbears. I’ve always referred to the definition from Eric Ries’ 2011 book The Lean Startup:

The smallest thing you can make or do, to test a hypothesis

But I hadn’t realised the phrase was originally coined in 2001, by Frank Robinson, as:

The smallest product to meet it’s desired market outcomes

I can see why these clash, and how the wording of Ries’ definition causes confusion.

The term has become overloaded where I work, often being used to refer to:

The scope that’s left once we’ve fixed the people working on the team, and the timeframe they have available.

I’m aiming to use the two alternative terms that Jeff Patton suggested, to be more specific in referring to the Robinson or Ries definition, respectively:

Smallest Successful Release

Next Best Test

Defining metrics for impacts and outcomes

This is pretty much what we’ve been doing on our work around self-referral into psychological therapies; figuring out what the key impact is, quantifying that, and then defining measurable outcomes that are leading indicators of us achieving that impact. We’ll do more on visualising this.

Hypotheses are going to hang around

I’ve used hypotheses to track user research experiments and activities, but I think a mistake we’ve made is to think that a hypothesis is done with, either validated or not, after our first experiment.

It’s fine to run a succession of experiments against a given hypothesis, each experiment becoming higher fidelity, as we learn more (see Giff Constable’s Truth Curve).

A hypothesis likely won’t be completely proven until we get something into production at scale. The earlier, lower-fidelity experiments allow us to stop earlier if a hypothesis is disproven.

Visualising multiple backlogs

We’ve tried before to visualise the end-to-end flow of work, from idea through to delivered user stories, and ended up ditching it in favour of a much simpler ‘Todo, Doing, Done’ type of board, for the whole team.

Jeff Patton showed some examples of separate backlogs and boards, for different types of work. I think we should have another go at this, embrace the idea that there are different types of Discovery and Delivery work going on, and visualise accordingly.

This also ties in with the ideas around dual-track development, another thing we could get more rigorous with. There were some great ideas around adapting your ‘scrum’ sessions to play towards these two different types of work going on.

Three ways of prioritising, for three different situations

These different types of work, and separate backlogs, should be managed and prioritised in different ways too:

New opportunities identified should be prioritised against our overall strategy or vision, to ensure we engage with things that keep us heading in that direction.

For Discovery activities we should prioritise based on what we need to learn the most about; assessing hypotheses based on risk and potential value.

Once we, as Product Managers, have defined a minimum successful release, then the team need to prioritise the user stories in that release based on a different set of criteria, such as:

What are the risks around feasibility of delivering this story
What else is dependent on this story
How likely is this to break something else
How long do we need to test this story

The Product Manager probably isn’t the best person to make these more granular prioritisation calls. Engineering are more qualified to understand a lot of the criteria above, based on believability-weighted decision-making.

Better Collaboration

Lots of tips on better collaboration – less talking, more intuition, stricter time-boxing.

I’ve often tried to include the whole team (maybe 8-10 people) in decision-making, but Jeff Patton made a good case for running sessions with fewer people. He talked about teams having a mix of deciders and executors, and having a core trio of Product Manager, Design Lead, and Engineering Lead, to lead on making a lot of decisions.

The course was technically a Certified Scrum Product Owner course, but the time we spent on Scrum itself was mainly focused on ways in which we can adapt it.

The things listed above are those sticking in my mind right now, but there was heaps of other good stuff over the two days, and loads to apply right away.

I had to leave early, so thank you, Jeffs.

What’s in a name – Owner, Manager, or Leader?

My esteemed colleague @benjiportwin just wrote a parting post which talks about job titles, and how much they matter, if at all.

He opened with the the Product Owner vs. Product Manager job title thing, which I’ve also been thinking about.

When I joined the NHS Choices team a few years back we had Product Leads who each looked after a specific area of the service. They did a great job of defining the changes needed for their particular products, but didn’t always interact directly on a day-to-day basis with the people building those products.

Changing titles to indicate change

We spent a couple of years changing this as we implemented agile methods across the programme. At the time I pushed for these roles to be called Product Owners, mainly because I wanted to force a distinction between the old and the new way, and that’s what the methodologies we were adopting (like Scrum) tended to call that role.

Shared ownership rules

I tend to associate the Product Owner role title with Scrum, and over time have gone off it a bit. Partly because I don’t like the idea of sticking with just one fixed methodology, and partly because it could imply one person having sole ownership of the product. I much prefer the idea of a team collectively owning the product that they build and run together.

Industry-standard

Instead I shifted towards the Product Manager job title. This seems to be much more of an industry-standard these days. If I see a Product Owner job ad I think “they do Scrum”, when I see Product Manager I think “they have Product teams”. Generalisations I know, but that’s what it conjures up in my mind.

Full circle

Most recently I’ve come back around to Product Lead. I like the idea of somebody leading the development of a product, rather than managing it. I think we all know the difference between a manager and a leader.

Managing a product could perhaps be read as holding it back, pruning it, keeping it in check (thanks to @st3v3nhunt for this). Whereas leading it talks of setting a vision, inspiring progress, and taking the product forward to exciting new places!

Does it matter?

I’ve thought about this mainly because I’ve been taking on a product role myself, but really, as Benji said in his post;

job titles are interchangeable and frankly unimportant, but what matters is the impact you make each and every day.

Good luck in NYC, Benji. See you on the sun deck!

Resources, or People?

Workplace language is interesting. We hear a lot of different jargon and cliches that we wouldn’t ordinarily encounter outside of the office. I think we know some of it is a bit silly and acknowledge it as such, but other workplace language is treated as totally normal.

One of the most common, but perhaps pernicious, examples of workplace language is the use of the word Resources, when we mean People. It really does seem to be workplace-only vernacular too – I’ve yet to hear anyone say “We need some more resources for 5-a-side tonight.”

I understand that it’s a fairly industry-standard term, but that doesn’t mean there aren’t issues with it. Lots has been written on this before – posts like this, and this – and there’s even a day dedicated to the cause.

oxforddictionaries.com defines resources as

A stock or supply of money, materials, staff, and other assets that can be drawn on by a person or organisation in order to function effectively

So technically speaking using the word resources to describe people isn’t wrong, and sometimes it makes sense to use the word resources to describe a particular ‘thing’. Resource management isn’t just about people – it could be about laptops, office space, or beanbags.

But 99% of the times I hear ‘resources’ mentioned at work, it’s being used to refer solely to people.

The problem is that the word resources seems to imply an interchangeable quantity –

“we need more resource”

“add some more resources”

“this resource is leaving, let’s get another one in”

From a management point of view this is great. It would be fantastic to be able to swap interchangeable resources in and out at will, in order to maintain performance.

But of course it doesn’t work like that. People have different skills, personalities, likes, dislikes, attitudes and so on. You cannot simply switch people in and out of a team, and expect things to continue at the same level or pace.

Because in knowledge work, value is generally delivered by teams, not individuals. A team is not just the sum of its parts – it’s the product of its interactions. The relationships between the people in the team determines the success of the team – it’s not about just adding up the raw skills of the individuals in the team.

The word resource obfuscates this fact. It helps us to kid ourselves that we can work in this way – swapping people around. It’s hiding the reality of the situation that when you’re dealing with knowledge work – people are not always going to be completely interchangeable.

That’s not to say I’m not against moving people around between teams on some regular basis. This can keep things fresh, and helps to share knowledge. But I think I’d get better results from trying out a new winger in my regular line-up, than swapping out the entire midfield.

I know a lot of people don’t like being referred to in this way, but I don’t think this is just about individuals being sensitive to being called a ‘resource’ – it’s about our cultural definition of how we view and treat our people, and about how we plan and manage work in a realistic way.

Having shared language is really important for building shared understanding, but next time you’re about to use the the word Resources, maybe pause and think; would the word People explain the situation in a clearer, more helpful, and more realistic way?

Building consensus around product ideas

I’ve spent the last year or so working with teams in the early stages of Product Discovery – examining the needs of users, and forming ideas and prototypes of services we can deliver to meet those needs.

One thing I’ve seen is the tendency in those teams to have the same conversations about a particular topic or idea several times over. Sometimes in the office, sometimes over lunch, and sometimes in the pub after work (which is where a lot of good ideas form).

This isn’t necessarily a bad thing while we’re shaping our ideas and building consensus in small groups. But once we’ve found ourselves repeating, and agreeing, the same concepts a few times, it feels like it’s time to get things out of our heads and onto some paper, so that we can share the idea further, and build a broader consensus.

The worst case scenario is if we don’t do this, that a small group forms an idea and assumes everyone else is also thinking the same thing. In the early stages of delivering a new service for users, building shared understanding across the whole team is critical.

Audio recording

A nice idea we tried recently was to get a small group of us (three worked nicely) to record the conversation. Kudos to @evilstreak for taking inspiration from the work @mattsheret has done with us on blogging.

We found a quiet space and used a USB mic (that we use for remote meetings) and Quicktime to record our conversation for about 30 minutes.

We didn’t write anything down beforehand, but the conversation was fairly structured, as we’d already had similar versions of it before.

One side-effect of the recording was that we were a bit more conscious of what we were saying, and avoided any unnecessary rambling. Being aware of the recording also stopped us from talking over each other at all. This is something we sometimes suffer from, as everyone has so many ideas to share, people just want to get them out there.

After the recording we transcribed it verbatim into a document. By sharing the audio file, two people were able to work in parallel for 30 minutes to get the whole conversation transcribed.

Pro-tip – using VLC to play back the conversation at a slightly slower speed (about 80%) allowed the typist to keep pace with the conversation without having to pause and replay bits. If you’re a really fast typist maybe you won’t need this.

Listening again to the recording actually helped ideas to crystallise in peoples’ minds. You were listening more intently, rather than thinking about what to say next, as you might in conversation.

Getting feedback from the wider team

As it was just three of us that had the initial conversation, we needed to gather feedback from the wider team.

Initially sharing the transcript was a useful way to share the ideas. Teammates reported that reading the transcript was a very natural way to read, and understand the ideas.

We then began to structure it into a more coherent narrative. Using a tool that enables quick electronic collaboration (like Google Docs) is really handy here. Everyone can be in the same version of the document at the same time – teammates can add comments, responses can be seen instantly, and everyone can see updates as they’re being made.

Crits

We supplement this electronic collaboration with group crit sessions.

Anyone interested in providing feedback gathers around a table and we read through some ideas and have a time-boxed discussion with the goal of gathering specific change to make to the narrative.

In this case we quickly realised that we didn’t have consensus across our team. Lot of new ideas came from these sessions, and the original narrative gave us a way of framing this discussion.

A picture speaks quite a few words

Another (fairly obvious) way of clarifying thoughts and ideas was to do quick sketches of your thoughts. Drawing something and showing it around was a really quick way of prompting further conversation to build shared understanding.

It’s handy to draw something and then pass it to a colleague without explaining what it shows, then ask them to explain their understanding of it.

Building consensus in public

So we’ve built some consensus amongst ourselves, within our team. Next we need to build some consensus with the wider world outside of our team – with our stakeholders and with the public.

We need to be open with our ideas as early as possible for a couple of reasons –

All the services we’re delivering are created for, and paid for by, the public. We should be transparent about how we’re spending public money.
The health and care system is complex. There are many different organisations involved. Being open about our ideas and proposals early on is a good way of getting the message out to these organisations, and starting a conversation with them.

One way in which we share our ideas openly is by blogging.

The document and drawing described above were drafted into an initial blog post by @evilstreak and @paul_furley, the drawing was redrawn by @demotive, and the resulting post is here – Booking is critical for transforming healthcare

Lego Flow Game

We run regular Delivery Methodology sessions for a mixture of Delivery Managers and other folk involved in running Delivery Teams. It’s the beginning of a Community of Practice around how we deliver.

One of the items that someone added to our list for discussion recently was about how we forecast effort, in order to predict delivery dates. Straight away I was thinking about how we shouldn’t necessarily be forecasting effort, as this doesn’t account for all of the time when things spend blocked, or just not being worked on.

Instead we should be trying to forecast the flow of work.

We’d been through a lot of this before, but we have bunch of new people in the teams now, and it seemed like a good idea for a refresher. My colleague Chris Cheadle had spotted the Lego Flow Game, and we were both keen to put our Lego advent calendars to good use, so we decided to run this as an introduction to the different ways in which work can be batched and managed, and the effect that might then have on how the work flows.

Lego Advent Calendar

The Lego Flow Game was created by Karl Scotland and Sallyann Freudenberg, and you can read all of the details of how to run it on Karl’s page. It makes sense to look at how the game works before reading about how we got on.

We ran the game as described here, but Chris adapted Karl’s slides very slightly to reflect the roles and stages involved in our delivery stream, and he tweaked the analyst role slightly so they were working from a prioritised ‘programme plan’.

Round 1 – Waterfall

Maybe we’re just really bad at building Lego, but we had to extend the time slightly to deliver anything at all in this first round! Extending the deadline, to meet a fixed scope, anyone?

The reason we only got two items into test and beyond was that the wrong kits were selected during the ‘Analysis’ phase for three items. The time we spent planning and analysing these items was essentially wasted effort, as we didn’t deliver them.

The pressure of dealing with a whole batch of work at that early stage took it’s toll. This is probably a fairly accurate reflection of trying to do a big up-front analysis under lots of pressure, and then paying the price later for not getting everything right.

It was also noticeable that because of the nature of the ‘waterfall rules’, people working on the later stages of delivery were sat idle for the majority of the round – what a waste!

Our Cumulative Flow Diagram (CFD) for the Waterfall Round looked like this –

You can see how we only delivered two items, and these weren’t delivered until 7:00 – no early feedback from the market in this round!

CFDs are a really useful tool for monitoring workflow and showing progress. I tend to use a full CFD to examine the flow of work through a team and for spotting bottlenecks, and a trimmed down CFD without the intermediate stages (essentially a burn-up chart) for demonstrating and forecasting progress with the team and stakeholders.

Round 2 – Time-boxed

We did three three-minute time-boxes during this round. Before we started the first time-box we estimated we’d complete three items. We only completed one – our estimation sucked!

In the second time-box we estimated we’d deliver two items and managed to deliver two, just!

Before the third time-box we discussed some improvements and estimated that we’d deliver three again. We delivered two items – almost three!

Team members were busier in this round, as items were passed through as they were ready to be worked on.

The CFD looks a bit funny as I think we still rejected items that were incorrectly analysed (although Karl’s rules say we could pass rejected work back for improvement)

The first items were delivered after 3:00 and you can the regular delivery intervals at 6:00 and 9:00, typical of a time-boxed approach.

Round 3 – Flow

During the flow round, people retained their specialisms, but each team member was very quick to help out at other stages, in order to keep the work flowing as quickly as possible.

Initially, those working in the earlier stages took a little getting used to the idea of not building up queues, but we soon got the hang of it.

The limiting of WIP to a single item in each stage forced us to swarm onto the tricky items. Everyone was busier – it ‘felt faster’.

We’ve had some success with this in our actual delivery teams – the idea of Developers helping out with testing, in order to keep queue sizes down – but I must admit it’s sometimes tricky to get an entire team into the mindset of working outside their specialisms, ‘for the good of the flow’.

Here’s the CFD –

The total items delivered was 7, which blows away the other rounds.

You can see we were delivering items into production as early as 2:00 into the round. So not only did we deliver more in total, but we got products to market much earlier. This is so useful in real life as we can be getting early feedback, which helps us to build even better products and services.

The fastest cycle time for an individual item was 2:00

A caveat

Delivering faster in the final round could be partly down to learning and practice – I know I was getting more familiar with building some of the Lego kits.

With this in mind, it would be interesting to run the session with a group who haven’t done it before, but doing the rounds in reverse order. Or maybe have multiple groups doing the rounds in different orders.

What else did we learn

* Limiting WIP really does work. The challenge is to take that into a real setting where specialists are delivering real products.

* I’ve used other kanban simulation tools like the coin-flip game and GetKanban. This Lego Flow Game seemed to have enough complexity to make it realistic, but kept it simple enough to be able to focus on what we’re learning from the exercise.

* Identifying Lego pieces inside plastic tubs is harder than you’d think.

Overall a neat and fun exercise, to get the whole team thinking about how work flows, and how their work fits into the bigger picture of delivering a product.

Failure IS an option

I wrote this post after coming off a daily ‘stand-up’ call where one Developer admitted he “didn’t know what he was doing” because he’s covering for one of our UI Developers while she’s off , and a DBA told us we weren’t seeing the data we expected that morning because he ran the wrong package by mistake.

It got me thinking about how it’s important to encourage an atmosphere where people aren’t afraid to talk about the mistakes they’ve made.

No-one admonished these people for saying these things. We respect someone for being open about the fact that they made a mistake, and then fixed it. We admire someone for actively stepping out of their comfort zone to work on something they’re not used to – it broadens their skills and reduces the number of single points of failure in our team – which in turn helps to keep our work flowing.

Whilst failure can be bad – it is also a chance to learn, and improve. It’s okay to make mistakes, and to admit when you don’t know the best way to do something, as long as you learn from it!

photo credit: ncc_badiey cc