This post looks at defining a blended innovation life cycle & an innovation readiness score – It builds on the previous post on Blended Innovation Model
Are we there yet?
Sharing progress on a revolutionary (or even an evolutionary) innovation becomes a challenge when not everyone speaks the same language – Core teams have worked the way they have for years and the MVIT operates with a completely different rule book (or at times; no rules).
A quick reference to the differences between the Core and the MVIT from a previous Blended Innovation Model post:
You are here (X)
Core teams generally function as a well-oiled machine and follow a SDLC that covers some, if not all of the following:
When looking at the interplay between the Core and the MVIT in a blended innovation engine we should look at how the MVIT lines up its efforts in relation to the existing SDLC (the well-oiled machine everyone is used to); Ideally we end up with two independent cycles that intersect or allow the movement (of products from the MVIT into the Core).
If we list out the various stages across development and implementation and assign responsibilities in the context of Revolutionary vs. Evolutionary innovation projects, we get a holistic view of where and when the MVIT is engaged.
For revolutionary/exploratory innovations – the MVIT (only) will start with POC’s and pilots in a vacuum to prove the value, and once it does, it will look at integrating with core to release the product in a limited scope for additional customer validation. Once larger validation has been performed the product will move to the core team for general availability. The matrix below helps illustrate the primary team(s) responsible for the slot/phase.
For Evolutionary/ Growth / Acceleration innovations – the idea has already been validated and the primary purpose in MVIT’s involvement is to help rapidly pilot and accelerate the development so that It can be integrated and added without negatively impacting the product roadmap. The Pilot and Limited stages are identical as there really isn’t a pilot phase. Once larger validation has been performed the product will move to the core team for general availability. The matrix below helps illustrate the primary team(s) responsible for the slot/phase.
Blended Innovation Life Cycle
Based on MVIT’s roles and efforts above – we can summarize and group MVIT’s role and efforts into 4 major phases and refer to it as the Blended Innovation Life Cycle (BILC):
During the MVP phase, the MVIT is focused on three progressive stages:
- Inception: Defining a very vague or high level idea that might seem like a good fit for the MVIT to work on.
- Fit: Refining the very vague/high level idea to answer “Does it fit?” – if we were to build this, can it integrate with the core product? How would it integrate? The focus here is on reaching an absolute Yes/No assessment on fit regardless of answering things like “when does it fit” or “how long will it take”.
- Pilot: MVIT will move forward and hack together a pilot that can be used for internal demos to showcase the idea – majority of the work is likely hardcoded or manually configured – the goal isn’t to make a finished product, but rather quickly show something that can help explain the idea and value add
It’s very likely that the MVIT never gets to stage 3 for majority of the ideas – but for the ones that do make it to the third stage – they then move to the next phase: “Viability”.
In the “Viability” phase the focus is on (internal) Customer Validation – the MVP is shown to the product team and other product roadmap stakeholders (like sales leadership) to assess business value. The product team would look at how the idea would enhance the product roadmap and would help define how the product would integrate with the core. A decision is made to move forward and to introduce to additional customers via limited availability.
In the “Production” phase, the focus is around Limited Availability stage – the MVIT works with the Core Product team to build a closer integration where architecture, integration approach, development, QA implementation and pre-sales plans are defined, development and implemented (by MVIT and Core). For customers who enter limited availability, the MVIT is responsible for supporting its product(s) where MVIT will not only provide front line support where needed, but also deploy and maintain deployment environments.
The “Scale” phase is focused on two final stages
- Transition: where the product and its support is transition to the core team – all artifacts, such as code, support guides, implementation guides, etc. are documented and handed over.
- Mainstream deployment: where the core team works with operations and support team to take over deployment and support.
By defining the “BILC” in the manner we did – where the core team becomes an integral part of the innovation directly after the pilot, we help implement a process that allows a natural alignment to the Core’s SDLC and we don’t end up with a team that’s releasing under-baked products that don’t integrate well with the core product.
We can also number each stage in the “Blended Innovation Life Cycle” to obtain an “Innovation Readiness Score” and we can then use both the score and the phases to help report on the readiness of an innovation and figure out where we are and what’s next.
This post looks at the blended innovation model within an enterprise – it expands on the previous post on A Start-up within an Enterprise
In a market segment/space, the portion that’s captured by an enterprise is its core. Outside this core is the new growth opportunity (the white space) that the enterprise has not (yet) captured; there can be additional enterprises in the same segment/space and over time the segment/space can increase and/or decrease – for the purpose of this post, we will assume that the segment/space stays the same.
For most (enterprise) organizations, the core is grown by the natural evolution of the products/services: as customers use the products/services their requests transform the roadmap. With (somewhat) uniform time and resources, focusing on everything all the customers ask for becomes a challenge and priority is given to the top tier customer base.
Most enterprises operate this way due to the low risk, as the needs have already been validated (due to customer demand). This type of innovation falls under evolutionary innovation.
For startups, the entire “new growth” opportunity becomes the initial target; as time goes on and effort is put into defining the product-market-fit a smaller “core” emerges. In many cases the (perceived) core might pivot several times (see below A -> B -> X) prior to eventually finding its eventual core (if it doesn’t completely fail by then).
The risk is much higher as customer validation still needs to happen, and significant time is spent in validation/product-market-fit. This type of innovation falls under revolutionary innovation.
When these two behaviors exist within their own respective entities (startup and enterprise) and are in the same space/segment they form a complementary relationship – which often results in the demise of the enterprise (unless the enterprise acquires the startup). The customers that are lower in priority for the enterprise move to the startup, either because the product is too feature rich, the needs are not met or they feel that the enterprise has become too big for them (low end disruption, See Clayton Christensen’s work on disruption). As they move out, the enterprise sees that as an opportunity to expand to the new (higher revenue) opportunity and move away from the lower end. As time goes on, the enterprise’s core continues to move outwards and the startup continues to encroach into the enterprises core until the enterprise has nothing left (eventually leading to the startup becoming its own enterprise).
The above describes the outcome when the two innovation modes are two different entities – but what if they were to be combined within an enterprise as a strategic initiative?
By making it a strategic initiative to combine both of these models within an enterprise to achieve a blended innovation engine; enterprises can greatly improve their competitive advantage and also accelerate their organic growth. With executive sponsorship, an additional dedicated team would need to be created (the MVIT).
A simple matrix can be put together to understand the differences between the core and the MVIT:
The interplay between the teams in a blended model is outlined below (to cover additional complexity a multi-core/multi-BU enterprise is used).
An enterprise that has multiple BU’s may cover different verticals in its “new growth” space; however, since each core operates in an evolutionary way, most do not cash in the opportunity to build organically within the shared (white) space.
There also needs to be some sort of “idea allocation engine” so that white space ideas (shared and non-shared among various BU’s), non-core customer requests and other exploratory ideas can be funneled into the appropriate team as there may be several ideas that seem “revolutionary”; but in-fact, they are actually more evolutionary in nature. The VCG (venture champion group) can help be the funnel to ensure that the MVIT is working on the appropriate opportunities (see:A Start-up within an Enterprise).
Once the idea generation and intake funnel is in place, the MVIT can begin piloting product for customer validation by releasing small pilots in the various spaces that iterate in functionality over time with customer involvement (as the viability becomes more obvious).
Developing the pilot in a common language/platform will help with the transition and once the pilot is ready, it would be supported by the MVIT. Should a pilot gain significant traction, the MVIT would continue to support it in a limited availability engagement and once a MVIT produced product enter limited availability, the BU should start planning for support, integration, release and productization under GA.
The integration/transition process from MVIT to Core will likely be significantly more involved than the other efforts.
Depending on the release and GA schedule, the Core will absorb the customer-validated pilot into the core – providing it a competitive advantage that was accelerated with the help of the MVIT that it would otherwise not have had.
A blended innovation model can greatly improve the competitive advance for an enterprise and also accelerate its organic growth. To successfully implement a blended innovation model it must be taken on as a strategic initiative, backed by executive sponsorship, have an additional dedicated team (MVIT), an idea allocation engine and a process for transition so that the investments in the blended model can be realized.
Evolution: a process of slow change and development.
Revolution: a sudden, extreme, or complete change in the way people live, work, etc.
Evolutionary innovation results in steady gradual growth over time whereas Revolutionary innovation results in rapid growth that eventually fizzles away (it needs another revolution to survive, or in most cases will become evolutionary over time). Both have risk – as a revolution can fail and an evolution can die out. (quick sketches to illustrate this below)
A blended model lets an organization take in (successful) revolutions and accelerate its growth, allowing it to extend its evolutionary life.
To accelerate innovation – both evolutionary and revolutionary should be leveraged and be a part of an organizations growth strategy; but thats easier said than done.
To build up and reflect on the previous learnings/posts the following is a summary on some crucial points that should be taken into account:
- Define the process and rules for evolutionary innovation and revolutionary innovation (the core team focuses on evolutionary and the MVIT focuses on revolutionary) as a strategic effort.
- Obtain executive sponsorship for the MVIT.
- Define GTM strategy and process for revolutionary innovations
- Communicate strategy to both top and bottom and get buy in.
- Budget and fund the MVIT.
- Reduce dependency and ensure the MVIT is a complete unit (has all the resources it needs and does not rely on others)
- Focus on execution.
- Optimize often.
- A dedicated “innovation” team that works outside the company’s core “processes” (a.k.a. red tape) does not exist
- You share or borrow resources from other teams who help out in addition to their core duties or have a “20% time” policy.
- A budget to spend on non-core R&D and other expenses was never factored in and/or approved.
- People expect the output from this “innovation” team to follow the same rate of return as your core product teams.
- You plan on engaging other (Architects, DevOps, Eng., etc.) core teams after all the work is done to come up with some sort of transition plan.
- No committed initial plan on what you will go after initially.
- No pass/fail metrics were setup.
- You do not have complete buy in from the top.
While all of the reasons above carry weight, if I had to pick one, it would be the first reason – the lack of a dedicated innovation team.
For most enterprises that have a part-time innovation team; all that innovation gets pushed aside when shit hits the fan – then its all-hands-on-deck – innovation, becomes an afterthought.
From a previous post: “It’s important for an enterprise to have a team that focuses on innovation as a “full-time strategic” activity and not as a “part-time ad-hoc” effort in order to have a greater chance of success with innovation – here is why: 75 % of venture-capital-backed start-ups fail; and 50% of backed start-ups make it to their 4th year. These startups, usually consist of dedicated entrepreneurial teams trying to build something, spending 100% of their energy, every minute of every hour trying to make it successful – they are in it full time. If a startup’s “full-time” innovation effort has such a low rate of success, what will be the success rate of a part-time effort?”
A dedicated team must be created if an enterprise wants to make innovation a strategic effort. If you have no one fully focused on innovation, you’ve decided not to focus on innovation.
Before we dive back into defining an approach that mixes Product and Custom focus, we should probably ask “How does one focus on the customer?”
In an ideal world there are no defects; but since there are, and customers expect them to be resolved, an ideal approach balances itself between being proactive and reactive; proactively resolve reported/discovered defects and appropriately manage escalations. On the surface, one focuses on the customer by making sure that the defects are fixed before a customer reports them and if a customer reports them, they are addressed promptly (top priority of course) and the customer is satisfied – below the surface, defect management and prioritization play an important role towards our customer focus as this tells us how soon we can (and will) actually resolve defects.
The list below doesn’t capture all possible approaches in resolving defects; it captures approaches that I have had some experience with (I recommend that you certainly do not try the first one):
Don’t resolve them
- Push the defect to the original developer, or the developer most familiar with the functionality for resolution.
- Allocate time for the first available developer to pull a defect in and resolve.
- Have a defect duty rotation where a person (or team) resolves only defects for a time period
- Have a dedicated team for defect resolution.
- … Some other create ways to resolve reported defects..
Always push to most familiar
Pushing the defect to the most familiar sounds like a great idea and in many cases it is because the one most familiar would be able to resolve quickest and positively impacts customer experience. The issue with this approach is that the most familiar person might be involved with something that has a higher priority than this defect, or is out on PTO and would not be able to resolve for another 2 weeks. Let’s say it takes someone familiar with the code to resolve in 1 hour but takes someone not familiar with the code 6 hours. If the defect goes to the person currently tied up and is most familiar, the customer will have to wait a minimum of 2 weeks + 1 hour; however, if it goes to the person not currently tied up and is least familiar, the customer will have to wait a minimum of 6 hours. Being collaborative and available for the team may improve the turnaround time on average, but a hard coded “always send to the one who created it” may not be the best approach.
Allocate time to pull
Allocating time towards the end of an iteration, development or whatever, towards “defect resolution” allows the team to first get the scheduled work out of the way, and “if” there is time, someone may pick something up from the backlog of defects. The issue with this approach is that if the development cycles are fully booked (maybe there is a hard date) and there is any risk or complexity that might lead to developers putting in all they have to meet the delivery; defect resolution gets thrown on the back burner. In most cases where the approach is “allocate time to pull defects”, the unspoken rule is that new products come first, defects second – unless; where the “unless” is for escalations and chaos/fire-fighting instances. For agile teams, if the time allocated towards defect resolution does not change from sprint to sprint, then there is no impact to velocity; however, if the time allocation is not fixed the velocity can get impacted depending on how much time is spent on defect resolutions (usually hours) vs. features (SP’s)…. You could estimate defects in story-points but this can lead to additional issues that will need to be worked out… i.e. do you really want to hold a sprint back? etc..
Defect resolution duty rotation
For a given time (usually the span of a sprint) a developer within a team, or a whole team themselves will be on defect resolution duty; once the time span is over, someone else (or a different team) takes on defect resolution duty and so on. This helps cross-train and helps make everyone familiar with the code base. It can also help improving code quality since everyone is learning from everyone’s mistakes and provides a great collaboration platform; while it does have some great benefits it does introduce some challenges. A significant issue is that developers and teams lose traction as they switch focus from “new product” to “old product”; the interruption can cause a delay since the developer(s) will need to get back to where they were after the rotation is over. For organizations that have many teams or larger teams this may be less of a concern since the rotation might happen every few months; but even then, when it does happen it does have a negative impact.
Dedicated team for defect resolution
The thought on this one is that if there is one team solely focused on supporting “released software” (defect/engineering sustaining team) and other team(s) focused on creating “new software” (Feature teams) that you end up with a two-tiered development approach where both the product and the customer can be focused on. The feature (new software) team is rarely impacted by defects from the “live” world and they can always focus on delivering new product; the defect/engineering sustaining team is dedicated to resolving defects and is not tied up with new features. The issue with this approach is that no one aspires to be a “defect fixer”, developers want to “develop” new and innovative “features” (or at least I did); It is possible to make this work if more attention is given to down-time cross-training, root cause analysis, collaboration, role rotations, etc… (I have seen teams evolve this approach into a “defect resolution duty rotation” approach)
In addition to the above, there can also be hybrid approaches that mix various approaches, i.e. defect resolution duty rotation with an added “pager duty” where someone (not on defect duty) is on-call but in general there is no “incorrect approach”; however:
Any approach can become incorrect when developers are forced to accept an approach that they do not agree with (or understand).
Any approach that is going to be implemented should be discussed with the teams that will be implementing it, focus on and explain the “why”. When an approach does not work, try to adjust it or try something else!
“if the code repository is an “elephant” and new code is peanuts being fed to this elephant by the other guys, then I am always cleaning up after the elephant; who wants to be a shit cleaner forever?”.
We are usually torn between building more “product” or satisfying the “customer”.
Prioritize Customer (maintaining product)
Fix and release to save the world
Prioritize Product (building more product)
Plan and build to a schedule
When you focus on product, you have a certain “amount” of product that needs to be built within a sprint (time box); you can plan for fixes by leaving some room for the defect backlog, but features come first – then come fixes, and the work is usually fixed where people know what they are working on for the sprint. In this scenario most will usually package after the sprint is over (test and release)
When you focus on customer, you have to fix and get the fix out the door ASAP. Priority is given to the most critical fix and/or customer and things will be packaged (test and release) as soon as appropriate and/or possible.
Some solve this by having a sustaining engineering team, but who really wants to only fix defects?; others use a mix of cross-functional or functional teams and adjust as needed, but this can be disruptive.
If you chose to “adjust as needed” (be agile) you will introduce some chaos every now and then but this can be minimized by having “plan of action”. How you adjust as needed and what type of “plan of action” you need also depends on what type of process you follow and what your focus is; is your culture focused on product? or is your culture focused on the customer? Depending on whom you ask (their role) within an organization, you may get different answers.
If you follow “Scrum” then your work queue is mostly “push” defined, where work is planned and pushed into a sprint/iteration before its worked on.
If you follow “Kanban” then your work queue is mostly “pull” defined, where work is pulled and worked on.
In an ideal world, one would have a process that allows the focus on both, the product and the customer. A process that allows you to “build what you say you will build” but also allow you to focus on “what is important right now”; such a process would mix Scrum and Kanban, giving you, ScumBan. The idea of a Scrumban is not new; there are books and many talks/posts regarding this. How Scrum and Kanban are merged together depend on the person who is cross-breeding the processes and what problem(s) they are trying to solve; I named my implementation “RAPID” for “Real-time Actionable Prioritized Individual Delivery”.
In my next post around RAPID, I will go over some examples that helped define the how and why behind RAPID and how it would be used in a team that wants to focus on both, the product and the customer.
People growth – Old blood vs New blood
I wrote my first post here on Jan 23 2011 and that post was titled “Startups – importance of your team“; Its been a little over 2 years since I wrote that post.
Most of us work 5 days a week, putting in about 8 or so hours a day (we will stick to the average/norm here). We come back home in the evening to spend anywhere from 1 to 4 hours with our family/friends.
When friends and/or acquaintances form a startup, the long hours and the close working relationship build on existing relationships and everyone at the startup works as a “family”; but what happens when there are no existing relationships? or what happens when you already have a family and someone new tries to come in? Wouldn’t it be awkward if you were out with your family/friends and a stranger joined your group and just hung out? would you be your self? most wouldn’t.
So how do you take an existing family (a started up culture) and add newer members to it? How do you mix the two so that you do not end up with friend circles?
I have 4 simple attitudes/behaviors that I build my base on:
“We are not that different”.
The new member see’s a whole new planet, different people, cultures, processes, jargon, etc. The first step should be to look for similarities between what they know and what they should know. For my teams I use a buddy system and its usually the previous newest member who buddies up with the new member. They go over materials, documenting anything new that might come up, go for lunch, talk about process, go through the who’s-who, engage the new person in conversations with the other team(s); they try to get to know this person as if they were dating each other.
“We got this, lets work on it together”.
How do you start work? where do you start? who do you ask? Scary questions for someone looking under the hood of something they do not understand. Here is where the buddy comes in again; during stand ups and sprint planning the buddy might offer “we can work on this together”, or someone else on the team might say “hey this is a good problem for me to show you how xyz works, and we can solve it”… they get the knowledge, they figure out how to start, they experience the process and they know how to close it. Build trust and accountability.
“Your team mentioned that you are catching on so quick, what can we improve?”
Over communicate reinforcement of team acceptance, ask for ideas on what can be improved, engage the new member; engaged employees have ideas and feedback that they want to share, things they have questions about.
“You are doing great, let me share my vision on how you play an important role to the team”
Setup a growth plan that’s challenging and communicate that it may be challenging and track to it. I like to plan for the 1, 3, 9, 12 and beyond and use data obtained directly or through peer feedback to gauge fit; if there is going to be tissue rejection, you need to act fast and figure out what you need to do to make it work successfully.
These 4 steps get you on track but you will still need to build additional on-boarding processes (around material and core knowledge ) that will grow the employees product knowledge. Its also important to keep your existing members in mind when you optimize culture as you want to grow the existing employees as well and not just the new ones.
At the end of the day it helps if we recognize that the teams we work with are more than just “Random people”; they are people we spend several hours with, they are friends, people we trust, can openly collaborate with and people we want to continue to work with.
When one finds a team they can work with for the rest of their life and can call family, its no longer “work”…it’s just a large friends & family gathering where they just happen to be working on something together and having fun.
We should all build and be part of such teams.
Is that what comes to your mind when someone mentions “process”? For many that’s a “Yes!”… “We don’t need no stinkin process; we just want to work”
“Process is just a book definition of something”, “its boring stuff”, or “Theory that doesn’t apply to the real world” are some of the phrases I have heard people use in disgust to define what process is; and in a past life someone used a “process is something that doesn’t apply to a startup or startup culture” on me….
“We care about people”
“We care about product”
“We only care about people and product”
..but what about process? why does process not get any love? What is it about process that makes people cringe? If process is evil, why is it that many methodologies (based on research and metrics) focus on the importance of all three (“People”, “Product” and “Process“)?
Process is everything that people and product are not.
- is culture and a shared understanding,
- it’s how your teams work and collaborate.
- it’s how you measure performance,
- its how you innovate, grow, plan and deliver product,
- it’s how you engage and grow people,
- Its more than ISO certification…
- its a lot more than this
Life is a process that’s filled with people and products
(among other things)
The takeaway from the previous post on KPI and metrics was that we should proactively monitor process and optimize as needed; just because it worked when you were a startup does not mean it will work when you are “startedup”, you will need it to scale and by capturing metrics and KPI’s you will be able to perform analysis when/if things go wrong. This however does not mean that you need process for the sake of having process or that you should focus on process over people; agility is important and being lean goes a long way.
The chicken and egg problem: What came first, the chicken, or the egg?
You have great team(s) and you have great product(s). Your team(s) is/are at capacity enhancing and maintaining the current product(s), but you need to create more product(s). In order to grow product(s) you need to add more people but these people need to be grown as well. Hiring people and not growing them will make product growth challenging as there will be a longer ramp up time or will disengage and leave (or you end up with an us vs them culture); and redirecting your current team to grow people rather than the current products will grow the new hires at a rapid pace but your current products will stop growing, what do you do? going back to the chicken and egg problem, I think in the long scheme of things it is irrelevant what came first; what is more important is the realization and existence of the chicken and egg, or the “idea” of a chicken and/or an egg, and that you need to ensure that the cycle continues, chickens give eggs and eggs (eventually) give chickens.
Single points of failure (Single Threads)
As engineers and architects we focus on identifying single points of failure within architecture; as managers we need to identify single points of failure within team members, processes and tools. Ask yourself, if I was to randomly start pulling people out (pto, resignations, etc) what would be the impact? Would we still meet delivery? Do we lose key subject matter experts? Most of the time people end up becoming single threads because there are many hats to wear and things need to get done; documentation and knowledge transfer becomes a “will get to it” task that many never get to.
Single points of failure and knowledge silos end up becoming a real impact to growth when you bring on new hires who need to be brought up to speed and grown because the same resources that need to help grow others are already busy with their existing work. Not only does it impact growth, it also negatively impacts collaboration and team culture, when people do not grow they disengage and this causes further issues. As you grow from a startup company with a smaller team to a “startedup” company with a larger and growing team, your single points of failure can grow and teams/members can get frustrated as they get pulled from different directions.
A few simple approaches to reducing and/or eliminating single points of failure are:
- Focus on collaboration and knowledge sharing among teams (culture), the more people share what they learn the more people know.
- Work-load for single threads can be split between product development and people development.
- On-boarding programs and training documentation can be built as part of a product backlog.
- New hires can be paired with senior resources to create mentor-ship and knowledge transfer programs.
Each organization is different and each has its unique attributes that require a solution or several approaches that solve the problem for that specific organization; a silver bullet approach doesn’t really work.
- To grow new product(s) outside your current capacity you need to grow team(s).
- To grow new team(s) who will grow new (products) your current team(s) can be impacted.
- Your current team(s) can end up becoming single threads and/or single points of failure.
- Recognize that this can become a problem.
- Focus on culture, collaboration, knowledge transfer, documentation, etc. so that the impact to the current team(s) and product(s) will be minimal and your new team(s) will rapidly grow and be engaged.
Several years ago I had a Volvo (88 760 GLE) and one day I noticed little streams of smoke from under the hood every time I would get back home; I had little experience with cars back then so I took it to a friend’s dads shop. I should have probably left when I got there because there was a customer yelling at him for messing up his beetle and charging him extra to fix it; apparently he put some hoses on wrong and then had to redo the work, I wasn’t there for the whole story, just the last 20 minutes of it and then the customer drove off.
My friend’s dad asked me to start my car and pull up next to him and leave the car running. He popped the hood and started to look around, he checked the hoses, looked at the pump, lines, drove it around, several hours passed by… he went from suggesting that there was coolant leak, to transmission leak to radiator oil leak… several more hours passed by as he came up with theories and looking at things… after being there for about 6 hours I decided to stick my head in and look at the engine block near the side where I told him to look and thought the smoke was coming from. Sure enough, just as I looked, I saw bubbles near the engine block’s cover, pointed it out to him and he said “ah, it’s loose! oil is getting out”; brought over his tools, tightened it and the problem solved.
I had been there for 7 hours, he wasn’t the type of guy who would say “this is my son’s friend, I am going to help him out”; he was a business man and to him I was a customer. I was upset with him for wasting 7 hours of my time; but what was really on my mind at that time was “how much will these 7 hours cost me?”, especially since he had a sign posted that had “Service hour rate: $45/hr” in big letters…. I will get back to this later in the post.
KPI and metrics
Man hours, hours, T-shirt size, story points, etc are measurements. I will try my best to not go down a rabbit hole with scrum, story point’s vs hour estimates… I will not! and hopefully I won’t lose my original messaging in all of this. Let’s start with this; at some point or the other, the focus and bottom line for a company will be “shipping product” against a “delivery schedule”. People, process, culture, story points, hour estimates, etc. will eventually stop existing if the “startedup” company cannot ship product and closes down (the focus here is shipping product according to other peoples expectations, i.e investors, C-suite, etc). With this at the back of our minds let’s continue on.
Story points are a measure of risk and/or effort and/or complexity (the and/or is there for the ones who disagree that story points do not measure complexity and/or risk).
Work/Task estimates are hours (usually) it takes to complete a task (with risk, complexity and effort already factored in).
Some argue that story points are just a block of time that provide the developers with padding; some argue that story points and hour estimates are not the same; some argue that time estimates need to be detailed and you should only use blocks of time (i.e. story points). I am not here to argue about any of these.
If you look at what part story points and sprints play: Story points (representing stories) go into sprints and sprints are boxed in time; at the end of the day, we are basically fighting for time. Others (Non-developers) usually want to know “how long will it take”, “when will it be done” because they need to set schedules, communicate to others, but (most) developers just want to work 🙂
How can I tell you how long it will take to fix when I have not even looked at the code; code that someone else wrote years ago!
When you have your team of 10 who have been working on a project (or two); the story points, velocity charts and estimations work out great. The team of 10 will negotiate points and the best suited person will do the work; everyone starts getting a good idea of what others and they themselves can do with improved accuracy (and velocity).
What risk can come up when you throw in 65 new hires and 2 new projects?
One thing that can happen is that the wrong person can get the wrong story; it is also possible that the new team may incorrectly estimate story points.
This happens or can happen because it takes experience and familiarity to get both (story point estimates and story assignment) of these right. Let’s say everyone is working on their tasks for a sprint, there is 1 story (something to do with SSL) remaining and it MUST make the sprint (which closes sooner than the story can be worked); the one developer available knows NOTHING about SSL, and a simple change measured as 2 story point remains, there is a developer on the team who knows about SSL but she is already working on a different feature that requires her knowledge on encryption.
Why did this get set as 2 story point when it was obvious to the team that there was risk? Rather than negotiate for 5 points the team settled for 2 because they expected the more senior programmer to have a better idea of how many story points it would take; the senior programmer saw no problem with 2, because in the past, her team was comfortable with it being 2. Repeat this several times, and you have a pattern; how do you break this pattern? or how would you even recognize this pattern? How would someone have suggested 5? How do you further refine estimating story points so that its not just based on gut, experience or familiarity? You start building and tracking additional KPI’s/metrics. Velocity and Burn Up/Down charts are common KPI’s that most use, you need more to help fish out patterns and gaps.
I think it’s important to acknowledge that in a true scrum setup (a perfect world, which is possible) these things may not happen (or happen rarely); if something doesn’t make a sprint, it moves to the next, but in most (all) of the places I have worked at, true scrums do not exist, shit happens and you cannot NOT make the dates; unless the team pulls together, works OT and possibly burns out (if it keeps happening).
As many others do, I like to base my estimation on experience and collectively agree with a team; but wouldn’t it be easier if there was another set of metrics that provided extra assurance or a reality check? i.e. historical data. Either metrics against tasks or metrics against similar stories. i.e. a story around “user login” averages to be a 4 point story based on previous similar stories; a task to “check credentials against db” takes 2 hours? The metrics can be captured after sprints/projects are done in adhoc meetings or release review meetings the data would be used for new hires, for times when things are under/over estimated. New hires and others could use this data to help estimate and understand gaps between what it takes on average and how the teams perform; the KPI’s would further detail teams health…
Going back to the Vovlo; I was waiting at his desk while he put his tools away, then he walked back to his desk, opened up a book, flipped pages to a section that read “Diagnostics”, found a line item for “Oil Leak” and sub-item “Gasket”, and said “2 hours, so you owe me $90 for fixing the problem”. Even though he spent 7 hours on it, he charged me for 2 because that’s what the book that had metrics for that type of service said it should take.
The Volvo example is important to me because it identifies performance issues; i.e. he should have done it in less than 2 hours if he was a good mechanic because that’s how long it takes on average; he should be asking himself “why did it take me more than 3 times as long and how can I do this better” because that’s what we would use similar development metrics for. “I seem to always under estimate UX changes, I need to pay better attention”.
The example I used has so far revolved around a startup company of 10 growing to a startedup company of 65; let me use a different example: A software development boutique is agile and they have client projects captured in back to back sprints. There are account executives that double as product owners who talk to the customers and based on experience and some dialogue with a few dev leads, they estimate effort and agree to a schedule and budget. Once they are ready to start the sprint (for a new project) the dev leads will update the team and as soon as sprint planning (stories placed) is done they start rolling.
A few issues:
- The dev lead and account executive time-boxed the maximum amount of time it can take based on their meetings with the customer; there was no team review
- Account executives double as product owners; their stories aren’t reviewed by developers until the work actually starts since developers are already busy on other projects
- There is no room for scope creep; things cannot get thrown out since this is a client project, and it must meet a date
- When there is scope creep and because its boxed; resources will work over time and burn out since the cycle just repeats it self – regardless of what your story points are, they have to fit in the sprints.
You could point out that the issue here is that there isn’t team involvement with the original estimation (for the time box) but this is because of how the company chooses to operate, so you cannot change this. You could state that the issue here is that there will always be some sort of scope creep so you cannot expect a hard stop but this is also because of how the company caters to customers expectations and needs to operate.
I would argue that the issue here is that the account executives do not have a “rate book” or “performance history” for similar tasks/stories that can help them come up with better estimates and factor in complexity when needed. In addition to that, since this company is in a pattern of running over (and solving by having people work over time, every time) there should be some sort of analysis done after each project to come up with “mistakes made” or “lessons learnt” so that people can learn from the patterns and put out better estimates; there will be times where you cannot change the entire companies culture, so instead you need to look for what can be improved.
With focus on additional KPI and metrics; one can identify issues with process or gaps before they become a bigger problem; Don’t just stick with how things worked when you were a startup and expect things to continue to always be perfect once you start growing, when you are “startedup” you need to start looking at adding new KPI’s and measurements that will help the bigger team work better and scale.