Tag Archives: process

OpenStack DefCore Process Draft Posted for Review [major milestone]

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OpenStack DefCore Committee is looking for community feedback about the proposed DefCore Process.

Golden PathMarch has been a month for OpenStack DefCore milestones.  At the March Board meeting, we approved the first official DefCore Guideline (called DefCore 2015.03) and we are poised to commit the first DefCore Process draft.

Once this initial commit is approved by the DefCore Committee (expected at DefCore Scale.8 Meeting 3/25 @ 9 PT), we’ll be ready for broader input by the community using the standard OpenStack Gerrit review process.  If you are not comfortable with Gerrit, we’ll take your input anyway that you want to give it except via telepathy (we’ve already got a lot on our minds).

Note: We’re also looking for input on the 2015.next Guideline targeted for 2015.04,

The DefCore Process documents the rules (who, what, when and where) that will govern how we create the DefCore Guidelines.  By design, it has to be detailed and specific without adding complexity and confusion.  The why of DefCore is all that work we did on principles that shape the process.

This process reflects nearly a year of gestation starting from the June 2014 DefCore face-to-face.  Once of the notable recent refinements was to organize material into time phases and to be more specific about who is responsible for specific actions.

To make review easier, I’ve reposted the draft.  Comments are welcome here and on the patch (and here after it lands).

DRAFT: OpenStack DefCore Process 2015A (reposted from OpenStack/DefCore)

This document describes the DefCore process required by the OpenStack bylaws and approved by the OpenStack Technical Committee and Board.

Expected Time line:

Time Frame Milestone Activities Lead By
-3 months S-3 “preliminary” draft (from current) DefCore
-2 months S-2 ID new Capabilities Community
-1 month S-1 Score capabilities DefCore
Summit S “solid” draft Community
Advisory items selected DefCore
+1 month S+1 self-testing Vendors
+2 months S+2 Test Flagging DefCore
+3 months S+3 Approve Guidance Board

Note: DefCore may accelerate the process to correct errors and omissions.

Process Definition

Continue reading →

To improve flow, we must view OpenStack community as a Software Factory

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This post was sparked by a conversation at OpenStack Atlanta between OpenStack Foundation board members Todd Moore (IBM) and Rob Hirschfeld (Dell/Community).  We share a background in industrial and software process and felt that sharing lean manufacturing translates directly to helping face OpenStack challenges.

While OpenStack has done an amazing job of growing contributors, scale has caused our code flow processes to be bottlenecked at the review stage.  This blocks flow throughout the entire system and presents a significant risk to both stability and feature addition.  Flow failures can ultimately lead to vendor forking.

Fundamentally, Todd and I felt that OpenStack needs to address system flows to build an integrated product.  The post expands on the “hidden influencers” issue and adds an additional challenge because improving flow requires that the community influences better understands the need to optimize work inter-project in a more systematic way.

Let’s start by visualizing the “OpenStack Factory”

Factory Floor

Factory Floor from Alpha Industries Wikipedia page

Imagine all of OpenStack’s 1000s of developers working together in a single giant start-up warehouse.  Each project in its own floor area with appropriate fooz tables, break areas and coffee bars.  It’s easy to visualize clusters of intent developers talking around tables or coding in dark corners while PTLs and TC members dash between groups coordinating work.

Expand the visualization so that we can actually see the code flowing between teams as little colored boxes.  Giving project has a unique color allows us to quickly see dependencies between teams.  Some features are piled up waiting for review inside teams while others are waiting on pallets between projects waiting on needed cross features have not completed.  At release time, we’d be able to see PTLs sorting through stacks of completed boxes to pick which ones were ready to ship.

Watching a factory floor from above is a humbling experience and a key feature of systems thinking enlightenment in both The Phoenix Project and The Goal.  It’s very easy to be caught up in a single project (local optimization) and miss the broader system implications of local choices.

There is a large body of work about Lean Process for Manufacturing

You’ve already visualized OpenStack code creation as a manufacturing floor: it’s a small step to accept that we can use the same proven processes for software and physical manufacturing.

As features move between teams (work centers), it becomes obvious that we’ve created a very highly interlocked sequence of component steps needed to deliver product; unfortunately, we have minimal coordination between the owners of the work centers.  If a feature is needs a critical resource (think programmer) to progress then we rely on the resource to allocate time to the work.  Since that person’s manager may not agree to the priority, we have a conflict between system flow and individual optimization.

That conflict destroys flow in the system.

The number #1 lesson from lean manufacturing is that putting individual optimization over system optimization reduces throughput.  Since our product and people managers are often competitors, we need to work doubly hard to address system concerns.  Worse yet our inventory of work in process and the interdependencies between projects is harder to discern.  Unlike the manufacturing floor, our developers and project leads cannot look down upon it and see the physical work as it progresses from station to station in one single holistic view.  The bottlenecks that throttle the OpenStack workflow are harder to see but we can find them, as can be demonstrated later in this post.

Until we can engage the resource owners in balancing system flow, OpenStack’s throughput will decline as we add resources.  This same principle is at play in the famous aphorism: adding developers makes a late project later.

Is there a solution?

There are lessons from Lean Manufacturing that can be applied

  1. Make quality a priority (expand tests from function to integration)
  2. Ensure integration from station to station (prioritize working together over features)
  3. Make sure that owners of work are coordinating (expose hidden influencers)
  4. Find and mange from the bottleneck (classic Lean says find the bottleneck and improve that)
  5. Create and monitor a system view
  6. Have everyone value finished product, not workstation output

Added Subscript: I highly recommend reading Daniel Berrange’s email about this.

OpenStack DefCore Process Flow: Community Feedback Cycles for Core [6 points + chart]

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If you’ve been following my DefCore posts, then you already know that DefCore is an OpenStack Foundation Board managed process “that sets base requirements by defining 1) capabilities, 2) code and 3) must-pass tests for all OpenStack™ products. This definition uses community resources and involvement to drive interoperability by creating the minimum standards for products labeled OpenStack™.”

In this post, I’m going to be very specific about what we think “community resources and involvement” entails.

The draft process flow chart was provided to the Board at our OSCON meeting without additional review.  It below boils down to a few key points:

  1. We are using the documents in the Gerrit review process to ensure that we work within the community processes.
  2. Going forward, we want to rely on the technical leadership to create, cluster and describe capabilities.  DefCore bootstrapped this process for Havana.  Further, Capabilities are defined by tests in Tempest so test coverage gaps (like Keystone v2) translate into Core gaps.
  3. We are investing in data driven and community involved feedback (via Refstack) to engage the largest possible base for core decisions.
  4. There is a “safety valve” for vendors to deal with test scenarios that are difficult to recreate in the field.
  5. The Board is responsible for approving the final artifacts based on the recommendations.  By having a transparent process, community input is expected in advance of that approval.
  6. The process is time sensitive.  There’s a need for the Board to produce Core definition in a timely way after each release and then feed that into the next one.  Ideally, the definitions will be approved at the Board meeting immediately following the release.

DefCore Process Draft

Process shows how the key components: designated sections and capabilities start from the previous release’s version and the DefCore committee manages the update process.  Community input is a vital part of the cycle.  This is especially true for identifying actual use of the capabilities through the Refstack data collection site.

  • Blue is for Board activities
  • Yellow is or user/vendor community activities
  • Green is for technical community activities
  • White is for process artifacts

This process is very much in draft form and any input or discussion is welcome!  I expect DefCore to take up formal review of the process in October.

Back of the Napkin to Presentation in 30 seconds

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I wanted to share a handy new process for creating presentations that I’ve been using lately that involves using cocktail napkins, smart phones and Google presentations.

Here’s the Process:

  1. sketch an idea out with my colleagues on a napkin, whiteboard or notebook during our discussion.
  2. snap a picture and upload it to my Google drive from my phone,
  3. import the picture into my presentation using my phone,
  4. tell my team that I’ve updated the presentation using Slack on my phone.

Clearly, this is not a finished presentation; however, it does serve to quickly capture critical content from a discussion without disrupting the flow of ideas.  It also alerts everyone that we’re adding content and helps frame what that content will be as we polish it.  When we immediately position the napkin into a deck, it creates clear action items and reference points for the team.

While blindingly simple, having a quick feedback loop and visual placeholders translates into improved team communication.

Supply Chain Transparency drives Open Source adoption, 6 reasons besides cost

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Author’s note: If you don’t believe that software is manufactured then go directly to your TRS80, do not collect $200.

I’m becoming increasingly impatient with people stating that “open source is about free software” because it’s blatantly untrue as a primary driver for corporate adoption.   Adopting open source often requires companies (and individuals) to trade-off one cost (license expense) for another (building expertise).  It is exactly the same balance we make between insourcing, partnering and outsourcing.

Full Speed Ahead

When I probe companies about what motivates their use of open source, they universally talk about transparency of delivery, non-single-vendor ownership of the source and their ability to influence as critical selection factors.  They are generally willing to invest more to build expertise if it translates into these benefits.  Viewed in this light, licensed software or closed services both cost more and introduce significant business risks where open alternatives exist.

This is not new: its basic manufacturing applied to IT

We had this same conversation in the 90s around manufacturing as that industry joltingly shifted from batch to just-in-time (aka Lean) manufacturing.  The key driver for that transformation was improved integration and management of supply chains.   We review witty doctoral dissertations about inventory, drum-buffer-rope flow and economic order quantity; however, trust my summary that it all comes down to companies need supply chain transparency.

As technology becomes more and more integral to delivering any type of product, companies must extend their need for supply chain transparency into their IT systems too.   That does not mean that companies expect to self-generate (insource) all of their technology.  The goal is to manage the supply chain, not to own every step.   Smart companies find a balance between control of owning their supply (making it themselves) and finding a reliable supply (multi-source is preferred).  If you cannot trust your suppliers then you must create inventory buffers and rigid contracts.  Both of these defenses limit agility and drive systemic dysfunction.  This was the lesson learned from Lean Just-In-Time manufacturing.

What does this look like for IT supply chains?

A healthy supply chain allows companies to address these issues.  They can:

  1. Change vendors / suppliers and get equivalent supply
  2. Check the status of deliveries (features)
  3. Review and impact quality
  4. Take deliverables in small frequent batches
  5. Collaborate with suppliers to manage & control the process
  6. Get visibility into the pipeline

None of these items are specific to software; instead, they are general attributes of a strong supply chain.  In a closed system, companies lose these critical supply chain values.  While tightly integrated partnerships can provide these benefits, they carry a cost premium and inherently limit vendor choice.

This sounds great!  What’s the cost?

You need to consider the level of supply chain transparency that’s right for you.  Most companies are no more likely to refine their own metal than to build from pure open source repositories.  There are transparency benefits from open source even from a single supplier.  Yet in some cases like the OpenStack community, systems are so essential that they are warrant investing as core competencies and joining the contributing community.  Even in those cases, most rely on vendors to package and extend their chosen open source software.

But that misses the point: contributing to an open source project is not required in managing your IT supply chain.  Instead, you need to build the operational infrastructure and processes that is open source ready.  They may require investing in skills and capabilities related to underlying technologies like the operating system, database or configuration management.  For cloud, it is likely to require more investment fault-tolerant architecture and API driven deployment.  Companies that are strong in these skills are better able to manage an open source IT supply chain.  In fact, they are better able to manage any IT supply chain because they have more control.

So, it’s not about cost…

When considering motivations for open source adoption, cost (or technology sizzle) should not be the primary factor.  In my experience, the most successful implementations focus first about operational readiness and project stability, and program transparency.  These questions indicate companies are thinking with an IT supply chain focus.

PS: If you found this interesting, you’ll also like my upstream imperative post.

Lean Process’ strength is being Honest and Humble

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Lean process and methodology is important to me because I think it is central to the work that we are doing in the community.  Even more, it’s changing how my team at Dell creates and delivers products for customers?
This post may be long, but my answer to “why Lean” ends up being very simple: Lean process is honest and humble.
I believe Lean process is more honest because it assumes a lack of knowledge.  It’s more “truthy” to admit there are a lot of things that we don’t know (we can’t know!) until we’ve started doing the work.  It’s very hard to admit we don’t have answers for things until we are further along because we want to feel like  experts and we to lock deliveries.
The “building software is like building a house” analogy is often used to claim that Lean lacks the design “blue prints” that other processes have.  The argument goes that builders needed to understand how the entire house works with structural support, plumbing lines and electrical circuits and things like that.  However, if I was going to build a house I would still leave a lot of things to the last-minute.  The process of building a house evolves so that the basic outlines of structural elements are known. In a lot of cases the position of rooms, the outlets, air conditioning ducts, a lot of the functional components, even windows and doors while they are often placed in the design can easily be moved and changed as you go through.  You can do a walk-through of a house after it’s been framed out and make all sorts of changes and adjustments.  As things go forward in the design of the house things become more and more difficult to change. You are building a brick façade, moving the windows within the façade are very difficult. However, interior places they aren’t.  Likewise, I don’t want to order my life-gem counter-tops from the blue-prints – it’s much safer to order off actual measurements.
Software projects are also building projects. You build a façade, you build a structure and within that structure you have a lot of flexibility. As you go you make more decisions and your choices become more limited. But, that is the nature of building.  For that reason, saying “we don’t know everything we want” is not just good practice, it is much more honest.
But honesty is not enough for a strong Lean process.  The need for humility in Lean architects and business people really stands out.  The Lean process is humble because it starts with the assumption that we don’t really understand the value, drivers, interests and features that make our product special.
We need very strong ideas and a vision; however, we need to be motivated by making something that is significant to other people.  They are the ones who give it value.
We have to give up the idea that we can convince someone who our idea will be significant to them – we have to show and collaborate instead.  The most important thing in building any project and taking any product to market is listening to the people who are using your product and understanding what their needs.  Instead of telling them what they need;  show them something interesting, interact with them and get their opinion.
Contrast that to waterfall methodology where the assumption is that we can put smart people in a room, have them figure out what the requirements are, build a team, get everything ready to go and then start executing.  That assumption is highly optimized and seems very efficient, but it has a huge amount of hubris in the process.  The idea that we can sit down two years in advance of market need and identify what those features and capabilities are seems outrageous to me in the current technology market.  It is so much harder to try to get that information correct and then execute on it that get a directional statement and begin and then get feedback and interact, it is a world of difference between the two processes.
Ultimately, Lean process about having requirements that are less defined or well-known.  It’s driven by giving respect to the people consuming the product.  We can hear their ideas and their reactions.  Where the users’ input can be evaluated and taken in to account.  It’s about collaboration.
Humility it not just about listening and collecting feedback: it is about interacting and building relationships.
So just as our customers are building a relationship with our product, they are also building a relationship with the people creating that product. And that relationship is what drives the product forward and what makes it a great product and it is what gives you a strong and loyal customer base, rather than dictating, “This is what you wanted. Here it is. I hope you enjoy it.”
This is a completely different and powerful way of delivering product.  I believe that honesty and humility in a Lean process inherently creates stronger products and ones that are both faster delivered and better suited to their markets.

How Good beats Great and avoids Process Interlock failure

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Note: This is part 2 of a 3 part series about the “process interlock dilemma.”

This post addresses how to solve the Process Interlock dilemma I identified in part 1. It is critical to understand the failure of Process Interlock comes because the interlocks turn assumptions into facts. We must accept that any forward looking schedule is a guess. If your guesses are accurate then your schedule should be accurate. That type of insight and $5 will get you a Venti Carmel Frappuccino.

The problem of predicting the future and promising to deliver on that schedule results in one of two poor outcomes.

  1. The better poor outcome is that you are accurate and committed to a schedule.

    To keep on the schedule, you must focus on the committed deliverables. While this sounds ideal, there an opportunity cost to staying focused. Opportunity cost means that while your team is busy delivering on schedule, it is not doing work to pursue other opportunities. In a perfect world, your team picked the most profitable option before it committed the schedule. If you don’t live in a perfect world then it’s likely that while you are working on deliver you’ve learned about another opportunity. You may make your schedule but miss a more lucrative opportunity.

  2. The worse poor outcome is that you are not accurate and committed to a schedule.

    In that case, you miss both the opportunity you thought you had and the ones that you could not pursue while staying dedicated to your planning assumptions.

Let’s go back to our G.Mordler example and look at some better outcomes:

The “we’re going to try outcome.”

The Trans Ma’am team, Alpha, Omega and the supplier all get together and realize that the current design is not shippable; however, they realize that each team’s roadmaps converge within target time. To reduce interlocks, Omega takes Alpha in the low power form and begins integration. During integration, Omega identifies that Alpha can produce sufficient power for short periods of time travel but causes the exhaust vent of the power module to melt. Alpha determines that a change to the cooling system will address the problem. In consulting with their supplier, Alpha asks them to stop design on the new supply and adjust the current design as needed. The resulting time drive does not meet GM’s initial design for 4 hour time jumps, but is sufficient for lead footed mommies to retroactively avoid speeding tickets. GM decides it can still market the limited design.

The “we’re not ready outcome. ”

The Trans Ma’am team, Alpha and Omega all get together and realize that the current design is not shippable in their current state. While they cannot commit each realizes that there is a different market for their products: Alpha pursues dog poop power generation for high rises condo towers (aka brown energy) and Omega finds military applications for time travel nuclear submarines. In the experience gained from delivering products to these markets, Alpha improves power delivery by 20% and Omega improves efficiency by 20%. These modest mutual improvements allow Alpha to meet Omega’s requirement. While the combined product is too late for the target date, GM is able to incorporate the design into next design cycle.

While neither outcome delivers the desired feature at the original schedule, both provide better ROI for the company. One of the most common problems with process interlock is that we lost sight of ROI in our desire to meet an impractical objective.

Process interlock is a classic case of point optimization driving down system-wide performance.

If you’re interested in this effect, I recommend reading Eli Goldratt’s The Goal.

In the part, I’ve discussed some ways to escape from Process Interlock. I’ll talk about four alternative approaches in part 3 (to be published 3/16).

The Process Interlock Dilemma – where Roadmaps get lost and why Waterfalls suck

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Note: This is part 1 of a 3 part series. I have been working on this series for nearly six months in an attempt to make this subtle but extremely expensive problem understandable. Rather than continue to polish the posts, I will post series for your enjoyment. I hope that it is enlightening, humorous or (ideally) both. Comments are welcome!

I’ve been struggling to explain a subtle process fail that occurs every day at my company (Dell) and also at every company I’ve ever worked with or for. I call this demon “Process Interlock” and it is the invisible bane of projects big and small. It manifests by forcing well-meaning product managers and engineering directors to make trade-offs that they know are wrong because of schedule commitments. It means that product quality consistently drops to the bottom of the list in favor of getting in that one promised feature. It shows up when customers get products late because of prospect who decided not to buy demanded a feature a year ago. These are the symptoms of the process interlock dilemma.

Process Interlock occurs when another team depends on your team for a future feature.

That sounds pretty innocuous right? It makes sense that other teams, customers and partners should be able to ask you about your roadmap and then build your delivery schedule into their plans. That is the perfectly logical request that happens inside my group every single day. Unfortunately, that exact commitment is what creates the problem because it locks your team’s velocity into the future and eliminates agility.

Note: I was reading chapter 11 in Eric Ries’ Lean Startup as was surprised to find him making very similar arguments but from a different perspective.

To hopefully help explain, I’m inventing a hypothetical project from the car division of the G.Mordler company. GM plans to add time travel as an option for their 2016 product line. They believe that there is a big market in minivan’s that can solve the proverbial “are we there yet problem” by simply skipping over the boring part of the trip. The trans-dimensional mommy mobile (or Trans Ma’am) will be part of a refresh of their 2014 model. The addition of a time circuit and power generator developed two internal divisions, Alpha and Omega, support a critical marketing event for the company so timing is important.

Let’s examine four outcomes of how these two divisions turn their assumed schedules into rigidly locked conundrum.

Scenario 0: Ideal Case.

Alpha makes the fusion power supply and Omega is making the time circuits. Based on experimental data, Omega’s design calls for 3.14 Gigawatts to operate their time capacitor; however, Alpha’s available design is limited to 0.73 Gigawatts. Alpha expects to reach 3.5 Gigawatts in 9 months when their supplier releases an updated nitrogen cooled super conductor. Based on that commitment, Omega has enough information to make an informed decision about their timeline. Since Alpha commits to deliver in 12 months (9 for the new part + 3 for development), Omega expects to deliver a working time circuit in 20 months (12 for the supply + 8 for development). In this example, there are 3 levels of Process Interlock: Alpha interlocks with the supplier and then Omega interlocks with Alpha. From a PERT schedule perspective, the world is now under control! It’s a brand new day and the birds are singing…

Scenario 1: Meet Schedule w/ Added Cost

Unfortunately, we now have a highly interlocked schedule. In the best case scenario (the one where we meet the schedule), Alpha has just signed up to meet an aggressive delivery timeframe. They have to put heavy pressure on the supplier to deliver their part which causes the supplier to increase the price for the cooler component. When their product manager identifies available alternative markets (such as power generating pet waste incineration), they are not able to purse the opportunities because they cannot risk the schedule impact of redirecting engineers. Meanwhile, Omega understands that a critical part is missing for 12 months and decides to reduce staffing while waiting for the needed part. In the process, they lose a key engineer who could have optimized the manufacturing process to half the production defect rate. Overall, the project meets schedule but at added cost, reduced quality and missed opportunities. This happened because the interlocks eliminated flexibility in the schedule for upstream and downstream participants. GM meets the launch window for the Trans Ma’am but high costs for the upgrade limit sales.

Scenario 2: Meet Schedule w/ Lost Features

A more likely “on schedule” alternative is that Alpha’s supplier cuts some corners to meet the aggressive deadline; consequently, power generation for Alpha is not reliable. This issue is not revealed by load testing in Alpha’s labs or short time travel testing by Omega. Instead, the faulty generators fail in integration field testing accidentally sending a DOT test driver home during rush hour traffic. Fixing the problem requires a redesign of the power plant. The new design does not fit into space allowed by the Trans Ma’am design team causing the entire program, while delivered “on time,” to be considered a failure and not shipped. GM misses the launch window for the Trans Ma’am.

Scenario 3:
Miss Schedule

In the most likely scenario the project is late. The schedule for Alpha slips because supplier requires an extra three months to meet the Alpha’s specs. In a common turn of fate, the supplier’s specs would be sufficient for Alpha to proceed; however, Alpha’s risk manager bumped up the cooling requirements by 20% in order to ensure they had wiggle room in their own design. Because of the supplier contract requiring delivery per spec, the supplier could not ship a workable but contractually unacceptable product. Since the part is delayed, Alpha has to slip the schedule to Omega. Compounding the problem, Alpha’s manager is optimistic that it will work out and does not alert Omega until 2 weeks before the deadline. Omega, who has been testing their circuits using liquid sodium cooled nuclear fission power plants, attempts to make up the schedule delay by imposing 20 hour Mountain Dew fueled work days. The aggressive schedule results in quality issues for the time circuits so that they can only be used during Mountain-time rebroadcasts of Seinfeld. After an unsuccessful bid to purchase the Denver cable TV station KDEV, GM misses the launch window for the Trans Ma’am.

I realize these examples are complicated, but I hope they humorously illuminate the problem.

In part 2, I’ll show an alternate approach for GM that addresses the process interlock.

Post Script

Of course, for this example, the entire project plan is a moot point since we’re talking about time machines! I’m offering two likely endings for the scenarios above:

The Pragmatists’ Ending: Once the project is finally complete, the manager simply drives the car back to the beginning of the project. Over white Russian martinis and sushi, her future self explains how the painful delivery schedule cost her the best years of her life causing her to quit. Her replacement cannot maintain funding for the project so it is eventually scraped by G.Mordler six months before the working pieces can be assembled.

The Realists’ Ending: Once the project is finally complete, the manager simply drives the car back to the beginning of the project. Over lemonade vodka tonics and tapas, her future self provides a USB stick with the critical design data needed to complete the project on time and budget. When she examines the data, the resulting time paradox creates a rift in the Einstein-Jacob space-time fabric thus ending the universe.

Process (not a dirty word!) means knowing how you make decisions

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“Process” is the least* understood business word.  I hear it talked about as something that must be added or introduced into various organizations so that they are more controlled.  Most typically, we tend to think of process as a synonym for “going to more meetings.”  So I want to set the record straight.

Process means knowing how your organization makes decisions.

There is nothing more to it than that.  If you know who will make a decision (the product manager), when they will make it (during the planning meeting), and what input they use to make the decision (a product roadmap) then you have a well defined process.  Ideally, you’d also know when you are able to influence the input (quarterly roadmap review or sprint retrospective).

Unfortunately, everyone wants to be able to make decisions all the time.  Making decisions all the time really means that you never make any decisions!  If there’s no agreed time, place, or person to make and communicate the decisions, it is impossible for anyone to know what’s the company is supposed to accomplish.

The default solution is to have meetings, meetings, and more meetings.  These meetings have lots of status updates, impassioned discussions, clever powerpoint slides and the appearance of consensus; however, they universally lack any commitment to execute work.  In the end, individuals doing work follow their own priorities or spin in the prevailing management wind.

So the next time someone suggests that your organization needs to work on a process, start by figuring out how you are going to make decisions.  After that, the rest of the process is just decoration.

* MRD ranks as a close second, but confusion is reduced since it’s as synonym and homophone for the French “merde.”

Screening Recruits for Agile Savvy

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We’re hiring new managers and developers into my team and its important (to me) that we find people who will embrace our Agile processes.

Sadly, many people experience with the fluffy Agile decorations and not its core disciplines; consequently, interviewees will answer “yes, I’ve done Agile” and not really (IMHO) know what they are saying.

So I wanted to craft some questions that will help identify good Agile candidates even if they have no experience (or negative experience) with the process.

  • Explain a time that you did not agree with a design decision that was being made. [Good candidates will tell you that they had a healthy debate about it, made sure they were heard, and then supported the team decision.  Excellent candidates will give you a specific case where they were wrong and the outcome was better their suggestion.]
  • How have you handled the trade-off between shipping quality software and getting a release done on time? [Good candidates will be pragmatic about the need to release but own quality as their responsibility.  Excellent candidates will talk about implementing TDD and automation so that quality can be maintained throughout a release cycle.]
  • How have you made changes to your work habits based on retrospectives? [Good candidates will tell you about items where they had to acknowledge other people’s suggestions and change their behavior.  Excellent candidates will be excited about having ownership in their team’s continuous improvement and can give examples.]
  • Why are sprint reviews important? [Good candidates will say that it’s important for a team to show progress to other groups.  Excellent candidates will tell you that it’s how a team shows that it is meeting its commitments and getting feedback to improve the product.]
  • Is it possible to achieve the objective to be “ship ready” at the end of each sprint? [Good candidates will say that ship ready is a great target but only practical in the last sprints before a release.  Excellent candidates will explain that being ship ready is a core driver for the process that ensures the team is focused on priorities, quality, and breaking work into components.]
  • Tell me about the best performing team that you’ve been part of. What made it a great team? [Good candidates will tell you about having quality people or a very tight focus.  Excellent candidates will tell you have the shared goals of the team and how people gave up individual recognition to accomplish team objectives.]
  • What does it mean to for a team to be transparent? [Good candidates will talk about status reports and documentation.  Excellent candidates will talk about being willing to take risks and fail fast.]

If they can’t pass theses questions then go buy a lifeboat.  You’ll want it for that that waterfall you’re going to be riding down shortly.