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!

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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?

My first User Research

Note – I originally posted this here on the NHS Choices blog back in February. It was written as three separate posts about User Research, from the point of view of someone who hasn’t been involved in this kind of thing before.

 

Over the last fortnight I’ve been observing User Research with my team, and it has been quite an eye-opener.

We’re at the point in our Discovery phase where we’ve made a bunch of assumptions about our users and their needs, and gathered information around these assumptions from various sources – on and off-site analytics, existing literature and research, social media, our service-desk tickets, and on-site surveys.

Now it’s time for us to talk directly to some USERS*

* Not all of the people we interview are necessarily users of the current NHS Choices service. Some of them might be potential users too.

User Research like this isn’t new to us. NHS Choices has had a dedicated Research team since 2007, but it’s in the last year or so that we’ve really started to more tightly integrate the work that the researchers do, into our delivery cycle. This is the first time we’ve involved the whole of the multi-disciplinary transformation team in observing and note-taking for the research sessions, doing the analysis and deciding on next steps within a couple of intensive research days.

Who do we interview?

For the two topics we’re focusing on right now – we’ve been talking to two distinct groups of people

  • Parents of children who’ve had Chickenpox in the last three months
  • People who sought a new Dentist in the last three months

We make sure we talk to a mixture of men and women from different socio-economic groups, of different ages, and with differing levels of internet skill.

We ask some quite detailed questions, so it’s good to get people who have had a relatively recent experience (hence the three month time-window) as the experiences they’re recalling will tend to be more accurate.

We use some dedicated participant recruitment agencies to source the specific people we want to interview. We supply a spec, like the parents described above, and they go and find a selection of those people. Obviously there’s a cost attached to this service, but the recruitment can be time-consuming, and it would be difficult to find a big enough cross-section of people ourselves.  Outsourcing this to an agency frees up our researchers to focus on the actual research itself.

The setup

We do some interviews in the participants’ own homes – interviewing people in their own environment gives us a much better sense of how people look for information and where this fits into their lives. Also we get to meet participants who would not want to go to a viewing facility.

We also do interviews in a dedicated research facility – these are the ones that the rest of the team and I have been observing.

We’ve used a couple of facilities so far, one in London, and SimpleUsability in Leeds – just a five minute walk from our Bridgewater Place office.

Our interviews have been one hour long. The participants sit with a researcher – who conducts the interview – and a note-taker in the interview room. The note-taker might be another researcher or other member of the team – we’ve had UX Architects and service desk analysts taking notes in our sessions.

With the participants, the researcher and the note-taker in the interview room, the rest of the team are behind a one-way mirror with the sound piped in, observing the whole show.

User Research Observation Room

And yes, with the one-way mirror, it fell to @seashaped and myself to make all the obligatory unfunny gags about being in a police interrogation scenario…

Interviewing

The interviews are based around a Topic Guide prepared beforehand by the researcher. This is based on input from our previous research, and includes specific subjects around which we want to learn more. The whole team feeds their ideas into the Topic Guide.

The interviews aren’t run strictly to the guide though – we’re talking to people about their lives, and the health of them and their families, so naturally the discussion can wander a little. But our researchers are great at steering the discussion such that we cover everything we need to in the interviews.

We decided not to put any prototypes in front of users in the first round of research. We’re trying to learn about users’ needs and their state of mind as they’re trying to fulfil those needs, so we didn’t want to bias them in any way by putting pre-formed ideas in front of them.

We did run a card-sorting exercise with users in the first round of Dental research – getting the participants to prioritise what would be most important to them when searching for a new dentist, by letting them sort cards.

We had a camera set up for the card-sorting exercise, so we could all see it clearly, without crowding around the mirror in the observation room.

Card Sorting

As the interview takes place, the note-taker is busy capturing all of the insights and information that come up. As the participant talks, the note-taker captures each individual piece of information or insight on a separate post-it note. This results in a lot of post-its – typically we’ve been getting through a standard pack of post-its per interview.

GDS have written in more detail about some note taking good practices.

Lots of post-its

Sorting into themes

Once the interviews are over, we have to make sense of everything the users have told us. We have a whole load of insights – each one logged on an individual post-it note. We need to get from what the users have said, to some actionable themes, as quickly as possible, without producing heavyweight research reports. We use the affinity-sorting technique to help us do this.

This basically involves us sorting all of the post-its into themes. We’ve been having a stab at identifying themes first, and then sorting the post-its into those groups first. As the sort takes place we’ll typically find that a theme needs to be split into one or more themes, or sometimes that a couple of existing themes are actually the same thing.

list of chickenpox themes

This isn’t the job of just the researcher and note taker who conducted the interviews. The whole team that’s been carrying out and observing the User Research takes part in this process, shifting post-its around on the wall until we feel we have some sensible groupings that represent the main themes that have come out of the interviews.

Dental Affinity Sorting

Chickenpox Affinity Sorting

Although we’re not presenting our research findings as big research reports or presentations, we are logging every insight electronically. After the sort, every insight gets logged in a spreadsheet with a code to represent the participant, the date and the theme under which the insight was grouped. We’re reviewing our approach to this, but the idea is that over time this forms our evidence base, and is a useful resource for looking back over past research, to find new insights.

Hypotheses

Once we have our themes we have to prioritise them and decide what to do with them next. At this early stage this usually means doing some more learning around some of the important themes. We’ve been forming Hypotheses from our Themes – I think this helps to highlight the fact that we’re at a learning stage, and we don’t know too much for sure, just yet.

We’ve been playing around with the format of these Hypotheses. As an example, one of the strong themes from our first round of User Research on Chickenpox was around visual identification. We expressed this as follows –

We believe that providing an improved method of visual identification of Chickenpox

for parents

will achieve an easier way for parents to successfully validate that their child has Chickenpox.

When testing this by showing a variety of visual and textual methods of identification to parents of children who’ve had chickenpox

we learned …

So we will

If you’re familiar with User Stories, you can see how this hypothesis would translate into that kind of format too. You could argue that all User Stories are Hypotheses really, until they’re built and tested in the wild.

Low-fidelity Prototypes

In order to test this hypothesis, we’re going to need some form of prototype to put in front of users. We’re working on a weekly cycle at present so we only have a few days before the next round of research. Speed of learning is more important at this stage, than how nice our prototypes look, so we’re just producing really low-fidelity prototypes and presenting them on paper.

For the visual identification hypothesis, here are some of the prototypes we’re presenting to users in our second round of research – see what I mean by low-fidelity, but this is just what we needed in order to explore the concepts a bit further, and learn a bit more.

Chickenpox prototype 1

Chickenpox prototype 2

We’ll base some of the questioning in our second round of research around these prototypes, and capture what we learn in our hypothesis template.

Based on this learning from the second round of research, we’ll either capture some user needs, write some new hypotheses to test, create some further prototypes to test, or maybe a mixture of all three.

Side effects

One interesting side-effect of our research sessions that we noticed was that some users were unaware of some aspects of our existing service, and as @kev_c_murray pointed out, some users left the sessions with an increased knowledge of what is available to them.

With comments like “Yeah I’m definitely going to go and look that up on your site now.” – we’re actually driving a little bit of behaviour change through the research itself. Okay, so if this was our behaviour-change strategy we’d have to do another 7 million days of research to reach the whole UK adult population, but every little helps, right…

What have we learned about how we do User Research?

  • The one week cycle of doing two full days of Research, then sorting and prototyping, is hard work. In fact it probably isn’t sustainable in the way we’re doing it right now, and we’ll need to adapt as we move into an Alpha phase.
  • Do a proper sound check at the start of the day – in both facilities we’ve used we’ve had to adjust the mic configuration during or after the first interview.
  • Research facilities do good lunches.
  • The observers should make their own notes around specific insights and themes, but don’t have everyone duplicating the notes that the note-taker makes – you’ll just end up with an unmanageable mountain of post-its.

More please

Lean UX BookWe plan to do much more of this as we continue to transform the NHS Choices service. As we move into an Alpha phase, we’ll continue to test what we’re building with users on a regular basis – we’ll probably switch from a one-week cycle to testing every fortnight.

As someone from more of a Software Development background, I find it fascinating to be able to get even closer to users than I have before, and start to really understand the context and needs of those people who we’ll be building the service for.

If you’re interested in reading more around some of the ideas in this post, try Lean UX – it’s a quick read, and talks in more detail about integrating User Research into an agile delivery cycle.

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’.

Boxes of Lego kits

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 –

Waterfall CFD

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.

You can read more about CFDs, and see loads of examples here.

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.

Timeboxed CFD

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 –

Flow 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.

A completed Lego kit

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.

10% time

We just launched a new initiative in our team to encourage more innovation and learning. Our 10% time is a bit of a cross between Google’s 20% time, and Dragons’ Den.

The idea is that any team members in Product Delivery can spend Friday afternoons working on their own project. It can be anything they want, but our panel of Dragons must agree to ‘invest’ a certain number of afternoons in the idea first.

Pitch

To get involved – team members deliver a short pitch explaining

  • what the idea is
  • how it will benefit the wider organisation
  • how long they initially need to work on it

dragons

Investment

The Dragons can choose to invest a certain number of afternoons in the idea, or ask for more refinements to the idea. When the end of the invested time comes – we’ll have demos of the different ideas, to see what we’ve come up with.

Ideas

There are some already some interesting ideas being pitched – ranging from a historic twitter analysis and a pregnancy care planner app, to a virtual fridge. Some people have pitched individually, and others have worked in pairs. The methodologies, technologies and tools used to build these ideas are entirely up the individuals building them, so it’s a chance to try out some new stuff.

 

 

Delivery, Delivery, Delivery

When I started this job it was towards the end of a big release. I witnessed a long and painful bug-fixing period, and got to thinking about what improvements could be put in place to make the next release smoother. It soon became apparent though, that the releases all year had been late, and as such a backlog of work had built up. What also became apparent was that all of this work was contractually required to be delivered by the end of 2010. My first full release was certainly going to be interesting, if not smooth…

According to the PMs all of the required work would fit into the time we had, but unfortunately the estimates that this assertion was based on had all been provided by individuals who would not actually deliver the work, or by developers who had been forced to ‘estimate’ to a specific figure. In my mind these so-called estimates are pretty worthless, as the whole point of estimating is to be able to plan well (in many environments it’s also to cost things up, but in our case the costs are already fixed by the overall contract), but more on estimation in a future post…

So we ended up in a situation with the resource, time and scope were effectively fixed – not ideal.

We mitigated this to a degree by ensuring we worked on the right things first. Although the overall scope was fixed, there are usually ‘nice-to-have’ features that the business can truly live without. The business owners weren’t used to having to prioritise in this way – we had to gain their trust, and explain that we weren’t planning to drop their features, rather we needed to avoid a situation where if the sh*t really did hit the fan, we wouldn’t be left with critical features not implemented, based on their advice. This seemed to work okay, and we had more confidence that we were working on the right things in the right order. We also tightened the testing feedback loop by getting the testers to test everything in an earlier environment. This reduced the total cycle time to deliver bug-fixed requirements.

Even after those minor improvements, it was a tough release. The team worked a lot of overtime, something I hope to avoid in future. We worked late nights and we worked from home some weekends. When we worked in the office at the weekend we had to get portable heaters in as it was so cold that our fingers were seizing up, and when it really started snowing we booked people into hotels so they could carry on working instead of leaving early.

And we delivered. We got the release out on time, and we partied when it was all over. Would I want to do another release like that again – no way… However there was something positive about the team pulling together to beat the odds. It was a time when we worked hard and played hard together, and it’s still one of the releases that some of those involved talk about with a wry smile.

Introducing Iterations

New year, new start… We’ve just got a big release under our belts and it feels like there is now enough trust from senior management to start making a few changes to the way we do things.

So what first..?

One problem seems to be the feedback loop from the business. They come up with an idea, it spends a few weeks/months being spec’d up, and then we develop it. Finally it gets tested and eventually the business owner gets to see the ‘finished’ product…

This sounds okay in practice, but it doesn’t work because things change along the way.

We need to tighten the feedback loop so the business are involved and engaged throughout the whole of the design, develop, and testing process.

Another problem is that time is wasted in spec’ing up features that never get delivered because we then run out of time in the development phase.

Ultimately we need to move away from the long phase-based waterfall approach that makes the flawed assumption that we can get everything right and complete in one phase before moving onto the next.

Pull?

I think the ideal solution to this will be to introduce a pull-based continuous-flow pipeline type of approach. We’d take one minimal marketable feature at a time and deliver it all the way through the pipeline from start to finish.

Although this type of Kanban approach says ‘start with what you do now’ – I see us having the problem that this is going to require a lot of regular communication and engagement between different teams, who work in different geographical locations. The organisation isn’t currently used to this level and style of communication.

Iterate

After some thought, I reckon it’s probably going to be better to try an iterative approach first.

We’ll try working in two week iterations; taking a small chunk of work at a time – maybe a couple of features – developing and testing them, and then finally demo’ing them to the business owners to get approval that we’ve done the right thing, and/or feedback that we need to change things.

By getting this early and regular feedback we should avoid the nasty surprise of finding we’ve delivered something incorrectly right at the end of a release when we don’t have the time to do anything about it. Ideally if something is going to fail, we want it to fail as early as possible! We can tackle high priority and high risk items in the earlier iterations, to drive out risk, and ensure we’re delivering the core requirements early on.

My reasoning of choosing iterations over continuous flow, is that because of our split site, it will be good to have specific markers in time where the different teams can come together to look at where we are, review progress and then plan the next steps to take.

I actually hope that over time the iterations might naturally disappear and we’ll end up with the continuous flow system that will work even better in the long run. Until then I think that introducing the discipline required to make an iterative approach work, will be a good thing…