One transformation technique Marty recommends is the Discovery Sprint. He recommends to do a Discovery Sprint when a team struggles to learn how to do product discovery, when the team has something big and critically important to solve or if the team is just moving too slowly. Marty talks more about it on his blog https://svpg.com/discovery-sprints/ and refers to the Book “Sprint” by Jake Knapp et al.
Another is named Pilot Teams. The idea behind the Pilot Teams is to create success within a smaller protected environment and convince doubtful or fearful or lazy people to follow the change process. The principle is borrowed from the technology adoption curve (aka “Gartner Hype Cycle”) – some people are early adopters, others are less eager. Chris Jones from SVPG talks about this technique in “Pilot Teams“. With these pilot teams the idea of A/B testing – well known from product development – can be applied to organization development as well.
Outcome-based Roadmaps is yet another way to start the transformation process. Simply continue working with product roadmaps, however introduce two differences. First, annotate every roadmap item with its associated expected business result. Every time this item is discussed highlight the expected business result. Second, after the launch of an roadmap item report immediately the actual result vs. the expected result. So, during the next 3-12 month the opportunity assessment information will get its way into the roadmap. For prioritization try to move away from prioritizing ideas to problems.
Common Product Discovery Pitfalls
Marty mentions several pitfalls he experienced and saw teams struggle with. He talks a lot more in his blog post on “Product Discovery: Pitfalls and Anti-Patterns“. Here’s just a summary and some notes.
Confirmation-biased Discovery The team and / or the stakeholders are not really interested in the results of Discovery, they just need affirmation.
Product as Prototype Discovery The team pretends working on a prototype implementation but it takes too long to actually get the prototype shipped (e.g. 4 month).
Partial Team Discovery Not Technology, UX and Product go see the customer, it’s only Product + UX.
One-Dimensional Discovery The team focusses only on quantitative or qualitative validation and draws wrong or incomplete conclusions.
Big Bang Discovery The team works on a single, big release shipped within a lengthy time frame. They don’t work in an iterative mode.
Outsourced Discovery The organization / stakeholders hired a “creative” agency to do the creative Discovery work. The implementation should then be picked up by the team.
Culture Baseline of successful companies
“If we get the culture right, most of the other stuff will happen naturally on its own.”
Tony Hiseh, CEO Zappos
Tackle Risks up Front
Value Risk – will they use / buy it?
Usability Risk – can they us it?
Feasibility Risk – can we build it?
Business Viability Risk – will our stakeholders support it?
Define Products Collaboratively, not Sequentially
Product Management
Product Design
Engineering
Focus on Business Results, not Output
Product teams exists to solve problems in ways that your customers love, yet work for your business.
This blog post is part of a series. It summarizes my personal notes of the workshop held by Marty Cagan “How to Create Tech Products Customers Love” from 5th to 6th of June in 2019 in San Francisco.
Variable compensation models and motivation – an experience report
We’re quite a young and digital organization. Our shareholder – a big publishing house – demands variable portions of the salary as a motivational factor. If that’s set in stone, you better look how to implement it best. Since 2015, we implemented variants of a variable compensation model and I’d like to share some of our learnings on the various models.
Salaries in the knowledge workers’ world
Today’s salaries usually have at least two components: the fixed part (paid usually every month) and the variable part (paid usually quarterly, twice or once per year). The fixed part represents the compensation for the working hours and fulfillment of the work contract. The variable portion can vary according to the agreed targets. Depending on the degree of achieving the targets the multiplier for the variable portion may vary from 0 to 1.5 or even higher.
Motivation and knowledge worker
My absolute favourite to understand motivation – and the impact of money on knowledge worker is the video by RSA describing Dan Pink’s thinking behind his book “Drive”: https://www.youtube.com/watch?v=u6XAPnuFjJc (10m 47s definitely worth watching!)
Motivation = three major ingredients: Mastery, Autonomy, Purpose.
Mastery is an intrinsic driver of knowledge worker. They want to improve their skills, they want to get better and better. A great workplace environment takes this into account and leaves room for people to practice, practice, practice. Autonomy gives people space to solve the problems they’re working on. Nobody tells them how to do so, nobody’s looking at the output. Only the outcome counts. Purpose sets the work activities into a greater context. Everything has a meaning, people understand why they do what they do. They see the greater picture, the vision. Purpose, in my opinion, is the most important ingredient for motivation. Put all three together as a fundament for a work environment and you have very likely intrinsically motivated people.
Money, on the other hand, as a benefit for work kills motivation. It is nice to receive your variable salary once, twice or 4 times a year. It’s a nice way for your boss to say “Well done, thank you!”. BUT the money is not a long lasting instrument to create or increase motivation (look at 2:12 into the video – they present research results there …).
So, why do we still have variable salaries to push motivation and output?
I know quite some young companies, some startups, some larger organizations who operate 100% on fixed salaries. They understood the basic principle of motivation and compensation. On the other side there are still some old, traditional and rusty organizations with variable compensation plans. Some decades ago, they connected the compensation to personal goals and never questioned themselves. Or it’s so common, they can’t even think about getting away from this model.
2015 – The “yearly revenue and individual targets”-model
Management sets a revenue target and every employee and his/her manager agrees individually on targets. The thesis behind the model: money is a key motivator to achieve top performance. The variable part of the salary is 100% connected to a company revenue goal and one or many individual goals.
We observed lengthy and excessive negotiations on individual goals with our employees. Even worse, the just-agreed goals hold just 4-6 weeks until they need refinement. Furthermore, we observed individuals stating they couldn’t help each other because this action would directly conflict with them achieving their goals. In essence, the model leads to people optimizing their personal benefits and defocusses company goals.
2016 – The “yearly revenue and department targets”-model
Management sets a revenue goal and each department head sets a yearly department target. The department target (e.g. “Reduce page load time to less than 2 seconds”) holds for the whole year and is always present. It will influence the way people work together but is not always a focus topic. The department target occurs in the variable compensation plans for all department employees. Thesis behind this model is again: money is a key motivator to achieve top performance. The variable portion of the salary is again connected 100% to the company revenue goal and one or many department goals.
Applying this model we observed less conflicts between individual employees. It’s quite time consuming during the identification of the department goals. They need strong alignment amongst each other. We managed to achieve quite good alignment – however had some occasions where people ended in conflicting department goal discussions. In the end the whole staff focussed ways more on achieving the department goals – better than with the previous model. However, the organization didn’t “feel” aligned on joint goals, more trying to achieve the department goals. Producing shiny winners on the cost of the overall company targets.
2017 – The “yearly revenue and quarterly company targets”-model
Don’t name the model OKR. We successfully burned OKR in 2014. Tried to implement it without external, experienced help. It ended in a process-by-the-book implementation and a perception of a grass-root democratic, inefficient and cluttered way to set 4 management and 4 team targets per quarter.
In this model, the management sets a yearly revenue target and company targets for the next 3 month. The company targets include everybody in the company – no matter what function or department. The targets need to be S.M.A.R.T. (Specific, Measurable, Achievable, Relevant, Timebound) and led to quite some discussion during definition – both between department heads and employees. The targets include e.g. specific product features, specific sales products or marketing activities. Thinking behind this model: everybody sits in the same boat and again money is a key motivator to achieve top performance. The variable portion of the salary is connected 100% to the company revenue goal and quarterly company goals.
During the implementation of this model we found “same company, same targets” led to some motivation for the active influencer for the goals (e.g. product, technology, sales, marketing) and quite some frustration for those having no influence at all (e.g. finance, HR, administration). They had to rely on their colleagues delivering the best job possible. On the other hand, we were able to set relevant goals for the next 3 month and were able to steer the company in a clever and agile way through the rough sea of economical changes. We had the staff members being focussed on achieving few topics of high relevance for the company.
We also learned – the hard way – that goal achievement communication can lead to some confusion and irritation if not done 100% transparent. And setting quarterly goals leads to quite some overhead to define goals every 12 weeks. Agility comes with a price tag!
2018 – The “100% guaranteed and 150% possible”-model
2017 ended with some really bad environmental messages for our business model. We needed to change quite some things. Amongst them was the variable compensation model. Our ambition at the time was to bring maximum calm to the staff members and allow them to focus on the company’s focus goals. One measure was to put away the variable portion of the compensation model. We guaranteed 100% of the bonus and made 150% possible if we achieved a specific traffic target earlier than we expected it.
Thinking behind this model is (see Dank Pink above): money doesn’t have any influence on work performance, but it has on work morale. We decoupled the compensation from achieving targets – allowing people to work on the company’s focus topics. And as a bonus, there is this 150% stretch goal. Nice to achieve – and desirable – but it just sits there.
We observed almost no discussion on compensation and fairness / unfairness of goals. People focused on getting the job done. I’d refer to the state of people as “intrinsic motivated”. At year end we didn’t manage to catch the 150% goal which led again to some frustration amongst the team. Furthermore, some specific departments (e.g. sales) perceive “100% fixed” less as an adorable state. For them it’s less motivating since their working model always follows includes “catching numbers”.
2019 – The “revenue and EBIT goal”-model
Beginning 2019 we found ourselves in a more stable environment and switched back to a variable compensation model. This time, we decided to focus on setting company wide financial goals. Everybody is able to influence them and the effort setting them is limited. The goal is set end 2018 for the whole year.
The thinking behind this model: money doesn’t have any influence on work performance, but it has on work morale. At a first glance, the model doesn’t look like an advancement but it effectively decouples financial goals from specialist topics. It’s the same for everybody and done once a year. So far, so good. It turns out to be a bit problematic since the environmental conditions changed quite a bit and the target corridors defined end 2018 are no longer achievable. So an adjustment is needed!
Which model worked best so far?
The 2015, 2016 and 2017 models worked better and better each year. Still having significant flaws with the direct connection between motivation and money paid. But the got better.
2018 was the most successful model so far. Less friction, lots of motivation and high pace – outcome over output. But we also had some frustration in performance-oriented departments (e.g. sales).
2019 doesn’t feel like an advancement from 2018. But 2019 is not over – let’s see.
The holy grail? Well, I don’t think we found it – so, we need to move on and adapt.
Software projects failed a lot in the past. They failed to deliver the value for the business, were too late or ways out of budget. The selected process method was usually the scapegoat for the failure with agile methods being the answer to any question in software development. But as usually in live, it’s not black or white. The selection of the right software process method depends on the surrounding of the project. I gathered some industry input and combined it to reflect the current thinking regarding agile software development methods vs. traditional methods.
The adapted Stacey matrix
The original stacey matrix supports decision making processes suggesting appropriate management actions and defines four areas: simple, complicated, complex and chaotic. The suggested actions depend heavily on the context of the decision making.
The dimensions of the adapted matrix: HOW and WHAT
The x-axis of the adapted matrix deals with the HOW. If the team knows the technology well and has used it many times before, we’re on the left. Otherwise, if the technology is completely new to the team we’re on the right of the dimension. The y-axis positions the WHAT. On the bottom of the axis, the stakeholder of the project all agree on the goals and have the same understanding of the expected outcome. On top it’s the opposite, no agreed requirements and no alignment on expectations. The individual mix of the project points to a certain area with a process model suggestion in the adapted matrix.
Waterfall …
Waterfall is a traditional project management method with sequential steps and no iterations. Massive upfront planning is done before any implementation work starts. If all goals and steps are clear, waterfall produces consistent results in a predictable and repeatable way. The clearly defined tasks lead to an optimized sequencing and optimal resource allocation. Waterfall optimizes resources and return on invest if cause and effects are clear to anybody in the project team.
… vs. Agile
Agile stands for SCRUM, Kanban and LEAN methods with flexibility, quick response and constantly changing environments in mind. They start quicker with smaller scope for the current increment with the scope being like a rolling window. Uncertainty of the projects’ goals needs quick adjustment and adaptation during the whole execution. Only close and frequent collaboration with all team members make agile projects successful. If causes and effects aren’t clear, agile works in small steps towards a value-generating and broadly accepted result.
Simple = easily knowable, the known knowns
Projects in the simple zone unveil very few surprises, decisions are fact- or evidence-based, advancement occurs in orderly, sequential steps and the WHAT is clear to anybody. Any size projects with clear activities and repeatable results fits in this category. It has been done multiple times before and best practices exist as benchmarks. The process is simple and could be handled in a check-list style.
Going forward in a simple, fully predictable project means reducing it to the maximum to make the single pieces easier to understand. Examples of simple: recipes, tasks on an assembly line, checklist based work.
Complicated = not simple but still knowable, the known unknowns
The complicated zone segments into socially and politically complicated and technically complicated. Complicated means less simple but still somewhat predictable.
In Social/political complicated environments people can not agree on the purpose of the project and the expectation on results is not clear. Requirements are conflicting amongst the diverse stakeholder which could be resolved with waterfall to get clearance on WHY before WHAT before HOW. On the other hand applying agile techniques could help convincing stakeholders to agree on already achieved results and smoothing the further requirements discussion. The project team needs to pay special attention on getting early agreement between stakeholders in place.
In technically complicated contexts it’s clear on WHY and WHAT to achieve. Still, the HOW is not clear. An agile iterative approach helps getting feedback from the project team on the achievements making adaptations possible.
Going forward in a complicated project means as well reducing it to the maximum to make the single pieces easier to understand. Technically complicated is e.g. using a specific technology for the first time. Political/social complicated is e.g. if the relation between cause and effect are not clear enough or conflicting opinions amongst various stakeholder exist.
Complex = not fully knowable but reasonably predictable, the unknown unknowns
The complexity zone stands for high risk and uncertainty and requires a high feedback frequency. Neither requirements nor the execution are clear. Holistic defined process methods don’t work any longer. The context asks for a more explorative approach with transparency, frequent inspection and adaptation. SCRUM as a process method in the toolbox of the agile mindset is the method of choice. It increases transparency with small iterations and frequent check-points allowing cheap adaptations. The team planning is the start point for each new iteration and allows immediate feedback from stakeholders to the teams to adapt the next iteration.
Complexity can not be reduced, some understanding can be achieved and complexity can not be planned, it simply grows. A good example of a complex project is software development in general. The requirements are rarely fully defined right at the beginning and it’s seldom clear which architectural solutions are superior to others.
Chaotic = neither knowable nor predictable, the unknowables
In chaotic zone requirements and execution path are both undefined and the risk is high. Kanban as the most flexible project management method is the tool of choice. With no structure like sprints and the only focus on work in progress (WIP) Kanban focuses on continuous delivering results to allow further modifications in direction and backlog items.
The goal is to move from chaotic towards complex by dividing the problems. The principle “Act, Sense and Respond” helps navigate towards the zone of complexity.
Innovation is usually part of agile product development methods. Sometimes, however, agile methods just replace other methods. SCRUM replaces Waterfall, KANBAN formalizes previously unordered work. Obviously, the innovation dilemma remains still open. Where comes the creativity from? The ideas? Where to test those hypotheses which are not part of the daily routine?
The hackathon as innovation tool
Some organizations run hackathons once or multiple times a year. We did and are doing this as well. We organized already 6 hackathons in the past. Once yearly. Did we see the innovation boost? Well, yes – and no.
How do we organize a hackathon?
A hackathon at gutefrage.net is a timeboxed activity (usually 2,5 days) and surrounded by a lot of social activities. We cook, we bake, we experience Virtual Reality, we do some board games, we play the football table and have a good time and fun. The whole company participates usually and is excited to validate hypotheses which are usually not part of the product development. There are no limits from a topic perspective. Teams organize themselves via a democratic voting exercise right at the beginning. People pitch their ideas and convince other people to become part of this specific project group.
What’s the typical outcome?
During the hackathons at gutefrage.net one out of five ideas launch during the hackathon. This one idea is production ready and creates value right from the launch. The other ideas typically proof aspects, create prototypes of various qualities, cover maximum the best-case implementation and still need an investment of 80% to be ready. The hackathon is a great team building event, it’s great for the morale, the culture. The hackathon drives people’s motivation and frustrates them if their project doesn’t make it into the finals.
What issues do we see?
The hackathon validates some hypotheses, some not and the question remains open what to do with all the started work? Will we follow some traces? Will we just abandon the work? Needless to say – after the 2,5 days hackathon there waits daily business in form of agile software development work. At gutefrage.net we promised to launch the winning idea and typically abandon the remaining work. We found that’s not the most efficient way to drive innovation.
The RocketLab – our way to innovate
As a learning organization we drew some conclusions from the hackathon experience. Mixed teams with participants from all relevant areas worked very well. The one project going live was a real push for team and company motivation. The others weren’t as good for morale. Thinking about this for a while we came up with a slightly different format – the RocketLab.
What’s different between RocketLab and the hackathon?
The RocketLab stands for outcomes and can potentially solve any topic: Product, Technology or others of cross-discipline relevance. At day one of the RocketLab there is one specific hypothesis the team focuses on. The team exclusively works for a defined period solely on solving this one issue. No distraction, just 100% focus. The team contains all disciplines to solve the issue on hand. They are all committed to create the best solution possible within the given time budget. It’s a team of maker, not talker, not theorists, no visionaries. The hackathon is broad and unspecific by nature, the RocketLab has a given goal to accomplish with the solution delegated 100% to the team.
How do we organize a RocketLab?
It’s typically either Product or Technology bringing up a specific hypothesis (or a technical complex problem to solve). A short discussion determines the amount of time we’re willing to spend on finding a solution – usually 3 to 5 days. The organizers invite people to participate in the RocketLab and the Lab kicks off. It’s never the whole company, only few people but interdisciplinary.
The initial task after kick-off is an intense planning session. The organizers introduce the hypothesis to a greater detail and the team sets goals – together with metrics. Right afterwards with a clear goal in mind and a good understanding of the metrics solution ideation starts. Ideally, the team ends this activity with a solid set of tasks for each team-member.
The RocketLab needs 100% dedicated team members – no excuses – and sits co-located in a special meeting room.
What’s the typical outcome?
The expected outcome of the RocketLab is a solution for the hypothesis from the beginning. The solution is live, up and running. If the team was not able to solve it 100% they have a clear understanding of the remaining efforts and a thorough plan. The plan is then executed in regular agile development work. One hypothesis, one implementation, one proof. The RocketLab is an efficient and effective tool to work concentratedly on a hypothesis – goal-oriented but very intense.
What issues do we see?
We did around 10 RocketLabs for very different topics. Very concrete, technical topics up to very abstract conceptual work. The results were sometimes simply spot on, other times needed further perfection during daily work. In essence, the RocketLab is a tool which borrows aspects from the hackathon but is more effective and efficient. It simply works for us and produced some very surprising solutions.
We still see some issues with the spill-over effect of the RocketLab – but that’s a minor problem. Only 20% of the Labs experienced the spill over.
The internet holds quite a lot of information. Here’s my favorite collection of tools, toolboxes, methods, best practices and howto’s from various fields of application. Most of them have a tight coupling to agile software development, agile organization development, product development and cross those fields.
Following a list of links and a short description of what to find on the site.
The site contains methods and tools around product Discovery and Delivery practices. The methods are collected by the community and serve to inspire seeking minds to test them in various situations. The methods are positioned in 4 main areas: Discovery, Delivery, Options Pivot and the Foundation.
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