In larger organizations, there are layers of managers, in a good way: teams aggregate to a manager, that layer of manager aggregates to another, then somewhere there’s executives, and, I don’t know, the mythical shareholder. Everyone has a boss. I want to discuss what it’s like to be the boss of all those managers and help them transform into all the existing, new fangled agile and digital transformation stuff. Most of the discussion I encounter is about individual staff and the product teams (those working on software or running it), but I don’t hear much about the management structures above those teams. Also, it’d be interesting to talk a little about what exactly things like “servant leadership” mean and how one manages their career (gets promotions, more compensation, etc.) when they’ve moved from being The Boss to a servant (to be tongue in cheek about it).
We’ve heard the notion of servant leadership, which sounds, you know, helpful. Can you give me an example of what that looks like though, like an actual one that happened?
I was watching a webinar that Jana did recently on her white paper. In the Q&A, they asked attendees something along the lines of “do you ever think of your organization’s vision and strategy, does it ever determine what you work on and how?” As I recall, almost zero percent of people responded yes. This seems like a critical tool for managers to use if they’re setting up autonomous teams that need to make decisions on their own – they need to know the principals, the goals. How should managers be moving beyond facile vision and strategy?
For years, I’ve heard about “the frozen middle,” managers who don’t want to change despite the urging and permission of executives (“above” them) and enthusem of staff (“below”). Is this cliche real? If so, what causes that frozen-ness?
(Following on from that), when you’re managing managers, what are you doing in this new, agile, world? Are you a servant to the servants?
There are occasionally “accidental managers” who sort of ended up there. But most of them have been pursing a career of going “up” the meatware stack. They want to grow their career, which usually means responsibilities, the glory and power that goes with it, and the rewards. So, if you’re a servant to people below you, how do you end up managing your career?
As you push responsibility down to teams, what are safety nets you put in place as they figure it out?
Developers often know what’s slowing them down better than executives. So, like, if you’re a manager, don’t let that happen. Go check on what’s actually going on in the organization instead of just what’s going on in your status meetings. Get the more details and free books mentioned at cote.pizza.
The only assignment I have is to ensure that my teams get the job done. It is an illusion that I can or should be hooked one-on-one. My task is to put a point on the horizon where all those people move with their knowledge and skills and then ensure that there is an optimal setting where they can function.
There’s a level of empathy needed for those on the frontline when making business decisions, especially decisions related to IT. Effective leaders are concerned with making the right call, said Gaffney. Ineffective leaders tend to implement practices and approaches that take small incremental de-risking steps, “led by dates and budgets and not happy humans.”
The key, I found, was to agree on new objectives. First, we tackled the question of documentation. In the old model, QA’s job was to make sure that documentation was complete—that each required section of the official template had been filled in with enough information to satisfy our overseers. But in conversation, the head of QA and I agreed that concisenesswas also an important aspect of quality. The project teams had been spending a lot of time writing text that was never read, creating documentation that was repetitive and in places inconsistent. Some sections of the templates made no sense for the types of projects we were doing. So the goal of QA, we agreed, should be to make sure that every document was as shortas possible and didn’t include any irrelevant information, even if that meant leaving template sections blank.
Of course this wouldn’t please our government overseers, who expected every section to be filled out in great detail, but that was my job to take care of—a kind of impediment removal. QA’s job was to ensure quality, which included concision and effective use of time. So QA began to demand simplifications to documents rather than insisting that they be padded with unnecessary words, and I went off to negotiate with overseers on their behalf.
The benefits of ditching the paper driving licence have been clear for a decade, but because of a fear of change, fear of failure and, yes, fear of digital, it hasn’t happened. We’ve forgotten the art of the possible.
Here’s an an idea for a formula for figuring out how much innovation an organization will do. I never know how good math is for this kind of thing, but it adds structure to programming an organization to be innovative, rather than career advancement seeking:
In organizations, the competing forces can be described as “stake in outcome” versus “perks of rank.” When employees feel they have more to gain from the group’s collective output, that’s where they invest their energy. When they feel their greatest rewards come from moving up the corporate ladder, they stop taking chances on risky new ideas whose failure could harm their careers.
Also, getting people to do new things by manipulating their desire to try new “tricks”:
Companies usually invest in training employees with the goal of better products or higher sales. Send a device designer to a technical workshop, and you’ll probably get better pacemakers. Send a salesperson to a speaking coach, and his pitch delivery might improve. But there’s another benefit: A designer who has learned new techniques will want to practice them. Training encourages employees to spend more time on projects, which reduces time spent on lobbying and networking.
The purpose of a sales force is to bring a company’s value proposition—its “deal”—to customers. That value proposition results in the development of a company’s “go-to-market” strategy, how it will implement that plan. Central to that activity can be a direct sales force, people who meet face-to-face with customers, a typical approach with complex and expensive equipment. For simple products, a catalog or store can suffice, and today even a simple website will do. In 1914, ITR’s and Hollerith’s products were complicated, and so one had to make a clear case about why customers should buy them.
There was considerable consistency across the decades about IBM’s value proposition. Watson explained to a new batch of executives that, “We are furnishing merchants, manufacturers and other businessmen with highly efficient machines which save them money.” For the larger IBM community, he followed with, “That is why we are going to make more money for this business.” He spoke about how IBM created value. By 1920, Watson was preaching that the way to accomplish C-T-R’s goals was “to serve better industry’s vital requirements—the need to conserve time, motions and money.” He introduced a signature for IBM sales literature, too, that delivered a sound-bite value proposition used for decades: “Speed, Accuracy, and Flexibility.”
people tend to assume that confident individuals are competent, when there is no actual relationship between the two qualities. Those confident people are then promoted. Overconfidence afflicts both sexes, but men more so; one study found that they overestimated their abilities by 30% and women by 15% on average.
These low-ball estimates are sometimes provided by consultants working to get their foot in the door, or by executive sponsors working to gain approval for their programs. Excluding low-ball estimates, the primary cause of poor estimates tends to be a lack of experience and background of the leader.
I get asked to talk with “executives” more and more. That’s part of why Pivotal moved me over to Europe. People make lots of claims about what executives want to hear, the conversations you can have with them as a vendor. They don’t have time. You have have to be concise. They don’t want to hear the details. They just want to advance their careers.
None of those are really my style, even part of my core epistemes. When I have a good conversation with anyone, it’s because we’re both curious about something we don’t know. The goal is to understand it, sort of hold it out on a meat-selfie-stick and look at it from all angles. This find that most people, especially people in management positions charged with translating corporate strategy to cash enjoy this. Some don’t, of course.
Anyhow, I’ve been writing down some common themes and “unknowns” for IT executives:
Innovation – use IT to help change how the current business functions and create new businesses. Rental car companies want to streamline the car pick-up process, governments want to go from analog and phone driven fulfillment to software, insurers want to help ranchers better track and protect the insured cows. Innovation is now a vacuous term, but when an organization can reliably create and run well designed software, innovation can actually mean something real, revenue producing, and strategic.
Keep making money – organizations already have existing, revenue producing businesses, often decades old. The IT supporting those businesses has worked for all that time – and still works! While many people derisively refer to this as “keeping the lights on,” it’s very difficult to work in the dark. Ensuring that the company can keep making money from their existing IT assets is vital – those lights need to stay on.
Restoring trust in IT’s capabilities – organizations expect little from IT and rarely trust them with critical business functions, like innovating. After decades of cost cutting, outsourcing, and managing IT like a series of projects instead of a continuous stream of innovation. The IT organization has to rebuild itself from top to bottom – how it runs infrastructure, how it developer and runs software, and the culture of IT. Once that trust is built, the business needs to re-set its expectations of what IT can do, reinventing IT back into everyday business.
What happens next is the fun part: how do executives reprogram their organization to do the above?
That’s my take on “to talk with executives,” then: learning what they’re doing, even validating my assumptions like the above. This is, or course, filled in with all sorts of before/afterr performance anecdotes (“proof points” and “cases”). Those are just conversational accelerants, though. They’re the things that move the narrative forward by keeping the reader engaged, so to speak, by keeping you interested (my self as well).
Anyhow. Even all this is a theory on my part, something to be validated. As I have more of these conversations, we’ll see what happens.
Anywhere there is lack of speed, there is massive business vulnerability:
Speed to deliver a product or service to customers.
Speed to perform maintenance on critical path equipment.
Speed to bring new products and services to market.
Speed to grow new businesses.
Speed to evaluate and incubate new ideas.
Speed to learn from failures.
Speed to identify and understand customers.
Speed to recognize and fix defects.
Speed to recognize and replace business models that are remnants of the past.
Speed to experiment and bring about new business models.
Speed to learn, experiment, and leverage new technologies.
Speed to solve customer problems and prevent reoccurrence.
Speed to communicate with customers and restore outages.
Speed of our website and mobile app.
Speed of our back-office systems.
Speed of answering a customer’s call.
Speed to engage and collaborate within and across teams.
Speed to effectively hire and onboard.
Speed to deal with human or system performance problems.
Speed to recognize and remove constructs from the past that are no longer effective.
Speed to know what to do.
Speed to get work done.
— John Mitchell, Duke Energy.
When enterprises need to change urgently, in most cases, The Problem is with the organization, the system in place. Individuals, like technology, are highly adaptable and can change. They’re both silly putty that wiggle into the cracks as needed. It’s the organization that’s obstinate and calcified.
How the organization works, it’s architecture, is the totally the responsibility of the leadership team. That ream owns it just like a product team owns their software. Leadership’s job is to make sure the organization is healthy, thriving, and capable.
DevOps’ great contribution to IT is treating culture as programmable. How your people work is as agile and programmable as the software. Executives, management, and enterprise architects — leadership — are product managers, programmers, and designers. The organization is their product. They pay attention to their customers — the product teams and the platform engineers — and do everything possible to get the best outcomes, to make the product, the organization, as productive and well designed as possible.
I’ve tried to collect together what’s worked for numerous organizations going through — again, even at the end, gird your brain-loins, and pardon me here — digital transformation. Of course, as in all of life, the generalized version of Orwell’s 6th rule applies: “break any of these rules rather than doing anything barbarous.
As you discover new, better ways of doing software I’d ask you to share those learnings a widely as possible, especially outside of your organization. There’s very little written on the topic of how regular, large organization managing the transformation to becoming software-driven enterprises.
Know that if your organization is dysfunctional, is always late and over budget, that it’s your fault. Your staff may be grumpy, may seem under-skilled, and your existing infrastructure and application may be pulling you down like a black-hole. All of that is your product: you own it.
As I recall, a conclusion is supposed to be inspirational instead of a downer. So, here you go. You have the power to fix it. Hurry up and get to work.
Signaling change with symbolic acts that embody the new culture is a good way to activate leadership characteristics quickly. For example, companies can designate meeting-free days to emphasize greater focus on action over planning, or they can give engineers a cash allowance to buy their own desktop equipment to demonstrate trust. Sometimes even a bold move, such as firing people whose behavior is antithetical to the new culture, is warranted. To signal change at Cisco, executives in certain divisions gave up their offices so the company could create team rooms; the company also started allowing employees to choose the workspace and tech tools that best fit their individual roles. The CEO of the North American software provider cited earlier began sending notes to employees who are praised by name in customer reviews. Such acknowledgment serves as an example of how company leaders can reinforce the customer-first mindset that’s central to the company culture.
By now, the reasons to improve how your organization does software are painfully obvious. Countless executives feel this urgency in their bones, and have been saying so for years:
“There’s going to be more change in the next five to ten years than there’s been in the last 50” — Mary Barra, CEO, GM
Intuitively, we know that business cycles are now incredibly fast: old companies die out, or are forced to dramatically change, and new companies rise to the top…soon to be knocked down by the new crop of sharp-toothed ankle biters.
Innosight’s third study of companies’ ability to maintain leadership positions estimates that by 2018, 50% of the companies on the S&P 500 will drop off, replaced by competitors and new market entrants. Staying at the top of your market-heap is getting harder and harder.
Profesor Rita McGrath has dubbed this the age of “transient advantage,” which is an apt way of describing how long — not very! — a company can rely on yesterday’s innovations. A traditional approach to corporate strategy is too slow moving, as she says: “[t]he fundamental problem is that deeply ingrained structures and systems designed to extract maximum value from a competitive advantage become a liability when the environment requires instead the capacity to surf through waves of short-lived opportunities.” Instead, organizations must be more agile: “to win in volatile and uncertain environments, executives need to learn how to exploit short-lived opportunities with speed and decisiveness.”
Software defined businesses
“We’re in the technology business. Our product happens to be banking, but largely that’s delivered through technology.” — Brian Porter, CEO, Scotiabank
We’re now solidly in an innovation phase of the business cycle. Organizations must become faster and more agile in strategy formulation, execution, and adaptation to changing markets. Again and again, IT is at the center of how startups enter new markets (often, disruptively) and how existing enterprises retain and grow market-share.
Organizations are seeking to become software defined businesses. In this mode of thinking, custom written software isn’t just a way of “digitizing” analog process (like making still lengthy mortgage applications or insurance claims processes “paperless”), but the mission critical tool for executing and evolving business models.
While software might have played merely a supporting role in the business for so long, successful organizations are casting software as the star. “It’s no longer a business product conversation, it’s a software product that drives the business and drives the market,” McKesson’s Andy Zitney says, later adding, “[i]t’s about the business, but business equals software now.”
Retail is the most obvious example. There’s an anecdote that Home Depot realized how important innovation was to them when they found out that Amazon sold more hammers than Homer. While other retailers languish, Home Depot grew revenue 7.5% year-over-year in Q4 2017. This isn’t solely due to software, but controlling its own software destiny has played a large part. As CIO Matt Carey says of competition from Amazon, “I don’t run their roadmap; I run my roadmap.”
These cases can seem pedestrian compared to self-driving cars and AIs that will (supposedly) create cyber-doctors. However, unlike these gee-whiz technologies, these small changes work incredibly fast and have large impacts.
Organizations often focus on the process, not the software
Most large organizations have massive IT departments, and equally large pools of developers working on software. However, many of these organizations haven’t updated their software practices and technologies for a decade or more. The results are predictable as three years of a Cutter Consortium survey shows. The study found that just 30% of respondents felt that IT helped their business innovate. As the chart below shows, this has fallen from about 50 percent in 2013:
This usefulness gap continues because IT departments are using an old approach to software. IT departments still rely on three-tier architectures, process hardened, dedicated infrastructure “service management” processes, and use functional organizations and long release cycles to (they believe) reliably produce software. I have to assume that this “waterfall” method was highly innovative and better than alternatives at the time…years and years ago.
In trying to be reliable and cost effective, IT departments have become excellent at process, even projects. In the 1990s, IT was in chaos with a shift from mainframes to Unix, then to Linux and Windows Server. On the desktop, the Windows GUI took over, but then the web browser hit mid-decade and added a whole new set of transitions and worries. Oh, and then there was the Internet, and the tail-end of massive ERP stand-ups that were changing core business processes. With all this chaos, IT often failed even on the simplest task like changing a password. Addressing this, the IT community created a school of thought called IT Service Management (ITSM) that sought to understand and codify each thing IT did for the business, conceptualizing those things as “services”: email, supply chain management, CRM, and, yes, changing passwords. Ticket desks were used to manage each process, and project management practices erected to lovingly cradle requests to create and change each IT service.
The result was certainly better than nothing, and much better than chaos. However, the ITSM age too often resulted in calcified IT departments that focused more on doing process perfectly than delivering useful services, that is, “business value.” The paladins of ITSM are quick to say this was never the intention, of course. It’s hard to know who’s the blame, or if we just need Jeffersonian table-flipping every ten years to hard reboot IT. Regardless, the traditional way of running IT is now a problem.
Most militaries, for example, can take anywhere between five to 12 years to roll out a new application. In this time, the nature of warfare can change many times over, a generations of soldiers can churn through the ranks, and the original requirements can change. Release cycles of even a year often result in the paradox of requirements perfection. In the best case scenario, the software you specified a year ago is delivered completely to spec, well tested, and fully function. But now, a year later, new competitor and customer demands nullifies the requirements from 12 months ago: that software is no longer needed.
Stretch this out to ten years, and you can see why the likes of US Air Force are treating transforming their software capabilities as a top priority. As General James “Mike” Holmes, Commander, Air Combat Command put it, “[y]ears of institutional risk aversion have led to the strategic dilemma plaguing us today: replacing our 30- year old fleet on a 30-year timeline.”
It’s easy to dismiss this as government work at its worst, clearly nothing like private industry. I’d challenge you, though, to find a large, multinational enterprise that doesn’t suffer from a similar software malaise. This misalignment is clearly unacceptable. IT needs to drastically change or it risks slowing down their organization’s innovation.
Small Batch Thinking
“If you aren’t embarrassed by the first version of your product, you shipped too late.” — Reid Hoffman, LinkedIn co-founder and former PayPal COO
How is software done right, then? Over the past 20 years, I’ve seen successful organizations use the same, general process: continuously executing small batches of software, over short iterations that put a rapid feedback loop in place. IT organizations that follow this process are delivering a different type of outcome than a set of requirements. They’re giving their organization the ability to adapt and change monthly, weekly, even daily.
By “small batches,” I mean identifying the problem to solve, formulating a theory of how to solve the problem, creating a hypothesis that can prove or disprove the theory, doing the smallest amount of application development and deployment needed to test your hypothesis, deploying the new code to production, observing how users interact with your software, and then using those observations to improve your software. The cycle, of course, repeats itself.
This whole process should take at most a week — hopefully just a day. All of these small batches, of course, add up over time to large pieces of software, but in contrast to a “large batch” approach, each small batch of code that survives the loop has been rigorously validated with actual users. Schools of thought such asLean Startup reduce this practice to helpfully simple sayings like “think, make, check.” Meanwhile, the Observe, Orient, Decide, Act (OODA) loop breaks the cycle down into even more precision. However you label and chart the small batch cycle, make sure you’re following a hypothesis driven cycle instead of assuming up-front that you know what how your software should be implemented.
As Liberty Mutual’s’ Chris Bartlow says, “document this hypothesis right because if you are disciplined in doing that you actually can have a more measurable outcome at the end where you can determine was my experiment successful or not.” This discipline gives you a tremendous amount of insight into decisions about the your software — features to add, remove, or modify. A small batch process gives you a much richer, fact-based ability to drive decisions.
“When you get to the stoplight on the circle [the end of a small batch loop] and you’re ready to make a decision on whether or not you want to continue, or whether or not you want to abandon the project, or experiment [more], or whether you want to pivot, I think [being hypothesis driven] gives you something to look back on and say, ‘okay, did my hypothesis come true at all,” Bartlow says, “is it right on or is it just not true at all?”
Long-term, you more easily avoid getting stuck in the “that’s the way we’ve always done it” lazy river current. The record of your experiments will also serve as an excellent report of your progress, even something auditors will cherish once you explain that log to them. These well-documented and tracked records are also your ongoing design history that you rely on to improve your software. The log helps makes even your failures valuable because you’ve proven something that does not work and, thus, should be avoided in the future. You avoid the cost and risk of repeating bad decisions.
This is the realm of multi-year projects that either underwhelm or are consistently late. As one manager at a large organization put it, “[w]e did an analysis of hundreds of projects over a multi-year period. The ones that delivered in less than a quarter succeeded about 80 percent of the time while the ones that lasted more than a year failed at about the same rate.”
No stranger to lengthy projects with, big, up-front analysis, the US Air Force is starting to think in terms of small batches for its software as well. “A [waterfall] mistake could cost $100 million, likely ending the career of anyone associated with that decision. A smaller mistake is less often a career-ender and thus encourages smart and informed risk-taking,” said M. Wes Haga.
Shift to user-centric design
If a small batch approach is the tool your organization now wields, a user-centric approach to software design is the ongoing activity you enable. There’s little new about taking a user-centric approach to software. What’s different is how much more efficient and fast creating good user experience and design is done thanks to highly networked applications and cloud-automated platforms.
When software was used exclusively behind the firewall and off networks as desktop applications, software creators had no idea how their software was being used. Well, they knew when there were errors because users fumed about bugs. Users never reported how well things were going when everything was working as planned. Worse, users didn’t report when things were just barely good enough and could be improved. This meant that software teams had very little input into what was actually working well in their software. They were left to, more or less, just make it up as they went along.
This feedback deficit was accompanied by slow release cycles. The complex, costly infrastructure used required a persnickety process of hardware planning, staging, release planning, and more operations work before deploying to production. Even the developers’ environments, needed to start any work, often took months to provision. Resources were scarce and expensive, and the lack of comprehensive automation across compute, storage, networking, and overall configuration required much slow, manual work.
The result of these two forces was, in retrospect, a dark age of software design. Starting in the mid-2000s, the ubiquity of always-on users and cloud automation removed these two hurdles.
Because applications were always hooked up to the network, it was now possible to observe every single interaction between a user and the software. For example, a 2009 Microsoft study found that only about one third of features added to the web properties achieved the team’s original goals — that is, were useful and considered successful. If you can quickly know which features are effective and ineffective, you can more rapidly improve your software, even eliminating bloat and the costs associated with unused, but expensive to support code.
By 2007, it was well understood that cloud automation dramatically reduced the amount of manual work needed to deploy software. The problem was evenly distributing those benefits beyond Silicon Valley and companies unfettered by the slow cycles of large enterprise. Just over 10 years later, we’re finally seeing cloud efficiencies spreading widely through enterprises. For example, Comcast realized a 75 percent lift in velocity and time to market when they used a cloud platform to automated their software delivery pipeline and production environment.
When you can gather, and thus, analyze all user interactions as well as deploy new releases at will, you can finally put a small batch cycle in place. And. this, you can create better user interaction and product design. And as we’ve seen in the past ten years, well designed products handily win out and bring in large profits.
Good design is worth spending time on. As Forrester consistently finds, organizations that focus on design tend to perform better financially than those that don’t. As such, design can be a highly effective competitive tool. Looking at the relationship between good design and revenue growth, Forrester found that organizations that focus on better design have a 14% lead on those that don’t. For example, “in two industries, cable and retail, leaders outperformed laggards by 24 percentage and 26 percentage points, respectively.”
I haven’t done a great job at describing what exactly good design looks like, let alone what the day-to-day work is. Let’s next look at simple case study with clear business results as an example.
The IRS historically used call centers to provide basic account information and tax payment services. Call centers are expensive and error prone: one study found that only 37% of calls were answered. Over 60% of people calling the IRS for help were simply hung-up on! With the need to continually control costs and deliver good service, the IRS had to do something.
In the consumer space, solving this type of account management problem has long been taken care of. It’s pretty easy in fact; just think of all the online banking systems you use and how you pay your monthly phone bills. But at the IRS, viewing your transactions had yet to be digitized.
When putting software around this, the IRS first thought that they should show you your complete history with the IRS, all of your transactions, as seen in the before UI example above. This confused users and most of them still wanted to pick up the phone. Think about what a perfect failure that is: the software worked exactly as designed and intended, it was just the wrong way to solve the problem.
Thankfully, because the IRS was following a small batch process, they caught this very quickly, and iterated through different hypotheses of how to solve the problem until they hit on a simple finding: when people want to know how much money they owe the IRS, they only want to know how much money they owe the IRS. When this version of the software was tested, most people didn’t want to use the phone.
Now, if the IRS was on a traditional 12 to 18 months cycle (or longer!) think of how poorly this would have gone, the business case would have failed, and you would probably have a dim view of IT and the IRS. But, by thinking about software in an agile, small batch way, the IRS did the right thing, not only saving money, but also solving people’s actual problems.
This project has great results: after some onerous up-front red-tape transformation, the IRS put an app in place which allows people to look up their account information, check payments due, and pay them. As of October 2017, there have been over 2 million users and the app has processed over $440m in payments. Clearly, a small batch success.
Create business agility with small batches
A small batch approach delivers value very early in the process with incremental releases of feature to production. This contrasts to a large batch approach which waits until the very end to (attempt to) deliver all of the value in one big lump. Of course, delivering early doesn’t delivering 1 year’s worth of work in one week. Instead, it means delivering just enough software to validate your design with user feedback.
Delivering early also allows you to prioritize your backlog, the list of requirements to implement. Organizations delivering weekly often find that a feature has been implemented “enough” and further development on the feature can be skipped. For example, to give people their hotel stay invoice, just allowing them to print a stripped down webpage might suffice instead of writing the code that creates and downloads a PDF. Once further development on that feature is de-prioritised, the team can decided to bring a new feature to the top of the backlog, likely ahead of schedule. This flexibility in priorities is one of the core of reasons agile software delivery makes business more agile and innovative.
Done properly a small batch approach also gives you a steady, reliable release train. This concept means that each week, your product teams will deliver roughly the same amount of “value” to production. Here, “value” means whatever changes they make to the software in production: typically, this is adding code that creates new features of modifies existing ones, but it could also be performance, security improvements, patches that ensure the software runs properly.
A functioning small batch process, then, gives you business agility and predictability. Trying out multiple ideas is now much cheaper, one of the keys to innovating new products and business models. The traditional, larger batch approach often requires millions of dollars in budget, driving the need for high-level approval, driving the need…to wait for the endless round of meetings and finance decisions, often on the annual budget cycle. This too often killed off ideas, as Allstate’s Opal Perry explains: “by the time you got permission, ideas died.” But with an MVP approach, as she contrasts, “a senior manager has $50,000 or $100,000 to do a minimum viable product” and can explore more ideas.
Case study: the lineworker knows best at Duke Energy
The team working on this went further than just trusting the VP’s first instincts, doing some field research with the actual line-workers. After getting to know the line-workers, they discovered a solution that redinfed the business problem. While the VP’s map would be a fine dashboard and give more information to central office, what really helped was developing a job assignment application for line-workers. This app would let line-workers locate their peers to, for example, partner with them on larger jobs, and avoid showing up at the same job. The app also introduced an Uber-like queue of work where line-workers could self-select which job to do next.
In retrospect this change seems obvious, but it’s only because the business paid attention to the feedback loop and user research and then reprioritized their software plans accordingly.
Transforming is easy…right?
Putting small batch thinking in place is no easy task: how long would it take you, currently, to deploy a single line of code, from a whiteboard to actually running in production? If you’re like most people, following the official process, it’d take weeks — just getting on the change review board’s schedule would take a week or more, and hopefully key approvers aren’t on vacation. This single-line of code thought experiment will start to flesh out what you need to do — rather, fix — to switch over to doing small batches.
Transforming one team, one piece of software isn’t easy, but it’s often very possible. Improving two applications usually works. How do you go about switching 10 applications over to a small batch process? How about 500?
Supporting hundreds of applications and teams — plus the backing services that support these applications — is a horse of a different color, rather, a drove of horses of many different colors. There’s no comprehensive manual for doing small batches at large scale, but in recent years several large organizations have been stampeding through the thicket. Thankfully, many of them have shared their success, failures, and, most importantly, lessons learned. We’ll look at their learnings next, with an eye, of course, at taming your organization’s big batch bucking.
Every journey begins with a single step, they say. What they don’t tell you is that you need to pick your first step wisely. And there’s also step two, and three, and then all of the n + 1 steps. Picking your initial project is important because you’ll be learning the ropes of a new way of developing and running software, and hopefully, of running your business.
When it comes to scaling change, choosing your first project wisely is also important for internal marketing and momentum purposes. The smell of success is the best deodorant, so you want your initial project to be successful. And…if it’s not, you quietly sweep it under the rug so no one notices. Few things will ruin the introduction of a new way of operating into a large organization than initial failure. Following Larman’s Law, the organization will do anything it can — consciously and unconsciously — to stop change. One sign of weakness early, and your cloud journey will be threatened by status quo zombies.
The USAF had been working for at least 5 years to modernize the 43 applications used in Central Air Operations Command, going through several hundreds of millions of dollars. These applications managed the US’s and allie’s daily air missions throughout Iraq, Syria, Afghanistan, and nearby countries. No small task of import. The applications were in sort need of modernizing, and some weren’t even really applications: the tanker refueling scheduling team used a combination of Excel spreadsheets and a whiteboard to plan the daily jet refueling missions.
Realizing that they’re standard 5 to 12 years cycle to create new applications wasn’t going to cut it, the US Air Force decided to try something new: a truly agile, small batch approach. Within 120 days, a suitable version of the tanker refueling application was in production. The tanker team continued to release new features on a weekly, even daily basis. The project was considered a wild success: the time to make the tanker schedule was reduced from 8 hours to 2, from 8 airmen to 1, and the USAF ended up saving over $200,000 a day in fuel that no longer needed to be flown around as backup for error in the schedule.
The success of this initial project, delivered in April of 2017, called JIGSAW, proved that a new approach would work, and work well. This allowed the group driving change at the USAF to start another project, and then another one, eventually getting to 13 projects in May of 2018 (5 in production and 8 in development. The team estimates that by January of 2018 they’ll have 15 to 18 applications in production.
The team’s initial success, though just a small part of the overall 43 applications, gave them the momentum to starting scale change to the rest of the organization and more applications.
Project picking peccadilloes
Picking the right projects to start with is key. They should be material to the business, but low risk. They should be small enough that you can quickly show success in the order of months and also technically feasible for using cloud technologies. These shouldn’t be science projects or automation of low value office activities — no augmented reality experiments or conference room schedulers (unless those are core to your business). On the other hand, you don’t want to do something too big, like migrate the .com site. Christopher Tretina recounts Comcast’s initial cloud-native ambitionsin this way:
We started out with a very grandiose vision… And it didn’t take us too long to realize we had bitten off a little more than we could chew. So around mid-year, last year, we pivoted and really tried to hone in and focus on what were just the main services we wanted to deploy that’ll get us the most benefit.
Your initial projects should also enable you to test out the entire software life cycle — all the way from conception to coding to deployment to running in production. Learning is a key goal of these initial projects and you’ll only do that by going through the full cycle.
The Home Depot’s Anthony McCulley describes the applications his company chose in the first six or so months of its cloud-native roll-out. “They were real apps. I would just say that they were just, sort of, scoped in such a way that if there was something wrong, it wouldn’t impact an entire business line.” In The Home Depot’s case, the applications were projects like managing (and charging for!) late tool rental returns and running the in store, custom paint desk.
A special case for initial projects is picking a microservice to deploy. Usually, such a service is a critical backend service for another application. A service that’s taken forever to actually deliver, or has been unchanged and ancient for years is an impactful choice. This is not as perfect a use case as a full-on, human-facing project, but it will allow you to test out cloud-native principals and rack up a success to build momentum. The microservice could be something like a fraud detection or address canonicalization service. This is one approach to migrating legacy applications in reverse order, a strangler from within!
Picking projects by portfolio pondering
There are several ways to select your initial projects. Many Pivotal customers use a method perfected over the past 25 years by Pivotal Labs called discovery. In the abstract, it follows the usual BCG matrix approach, flavored with some Eisenhower matrix. This method builds in intentional scrappiness to do a portfolio analysis with the limited time you can secure from all of the stakeholders. The goal is to get a ranked list of projects based on your organization’s priorities and the easiness of the projects.
First, gather all of the relevant stakeholders. This should include a mix of people from the business and IT sides, as well as the actual team that will be doing the initial projects. A discovery session is typically led by a facilitator, preferably someone familiar with coaxing a room through this process.
The facilitator typically hands out stacks of sticky notes and markers, asking everyone to write down projects that they think are valuable. What “valuable” means will depend on each stakeholder. We’d hope that the more business minded of them would have a list of corporate initiatives and goals in their heads (or a more formal one they brought to the meeting). One approach used in Lean methodology is to ask management this question: “If we could do one thing better, what would it be?” Start from there, maybe with some five whys spelunking.
Participants then put up their sticky notes in the quadrant, forcing themselves not to weasel out and put the notes on the lines. Once everyone finishes, you get a good sense of projects that all stakeholders think are important, sorted by the criteria I mentioned, primarily that they’re material to the business (important) and low risk (easy). If all of the notes are clustered in one quadrant (usually, in the upper right, of course), the facilitator will redo the 2×2 lines to just that quadrant, forcing the decision of narrowing down to just projects to do now. The process might repeat itself over several rounds. To enforce project ranking, you might also use techniques like dot voting which will force the participants to really think about how they would prioritize the projects given limited resources.
At the end, you should have a list of projects, ranked by the consensus of the stakeholders in the room.
Planning out the initial project
You may want to refine your list even more, but to get moving, pick the top project and start breaking down what to do next. How you proceed to do this is highly dependent on how your product teams breaks down tasks into stories, iterations, and releases. More than likely, following the general idea of a small batch process you’ll
Create an understanding of the user(s) and the challenges they’re trying to solve with your software through personas and approaches like scenarios or Jobs to be Done.
Come up with several theories for how those problems could be solved.
Distill the work to code and test your theories into stories.
Add in more stories for non-functional requirements (like setting up build processes, CI/CD pipelines, testing automation, etc.).
Arrange stories into iteration-sized chunks without planning too far ahead (least you’re not able to adapt your work to the user experience and productivity findings from each iteration)
The chart measures application instances in Pivotal Cloud Foundry, which does not map exactly to a single application. As of December 2016, The Home Depot had roughly 130 applications deployed in Pivotal Cloud Foundry. What’s important is the general shape and acceleration of the curve. By starting small, with real applications, The Home Depot became learned the new process and at the same time delivered meaningful results that helped them scale their transformation.
If a strategy is presented in the boardroom but employees never see, is it really a strategy? Obviously, not. Leadership too often believes that the strategy is crystal clear but staff usually disagree. For example, in a survey of 1,700 leaders and staff, 69% of leaders said their vision was “pragmatic and could easily translated into concrete projects and initiatives.” Employees, had a glummer picture: only 36% agreed.
Your staff likely doesn’t know the vision and strategy. More than just understanding it, they rarely know how they can help. As Boeing’s Nikki Allen put it:
In order to get people to scale, they have to understand how to connect the dots. They have to see it themselves in what they do — whether it’s developing software, or protecting and securing the network, or provisioning infrastructure — they have to see how the work they do every day connects back to enabling the business to either be productive, or generate revenue.
There’s little wizardry to communicating strategy. First, it has to be compressible. But, you already did that when you established your vision and strategy…right? Next, you push it through all the mediums and channels at your disposal to tell people over and over again. Chances are, you have “town hall” meetings, email lists, and team meetings up and down your organization. Recording videos and podcasts of you explaining the vision and strategy is helpful. Include strategy overviews in your public speaking because staff often scrutinizes these recordings. While “Enterprise 2.0” fizzled out several years ago, Facebook has trained all us to follow activity streams and other social flotsam. Use those habits and the internal channels you have to spread your communication.
You also need to include examples of the strategy in action, what worked and didn’t work. As with any type of persuasion, getting people’s peers to tell their stories are the best examples. Google and others find that celebrating failure with company-wide post mortems is instructive, career-ending crazy as that may sound. Stories of success and failure are valuable because you can draw a direct line between high-level vision to fingers on keyboard. If you’re afraid of sharing too much failure, try just opening up status metrics to staff. Leadership usually underestimates the value of organization-wide information radiators, but staff usually wants that information to stop prairie dogging through their 9 to 5.
As you’re progressing, getting feedback is key: do people understand it? Do people know what to do to help? If not, then it’s time to tune your messages and mediums. Again, you can apply a small batch process to test out new methods of communicating. While I find them tedious, staff surveys help: ask people if they understand your strategy. Be to also ask if know how to help execute the strategy.
Manifestos can help decompose a strategy into tangible goals and tactics. The insurance industry is on the cusp of turbulent competitive landscape. To call it “disruptive,” would be too narrow. To pick one sea of chop, autonomous vehicles are “changing everything about our personal auto line and we have to change ourselves,” says Liberty Mutual’s Chris Bartlow. New technologies are only one of many fronts in Liberty’s new competitive landscape. Every existing insurance company and cut-throat competitors like Amazon are using new technologies to both optimize existing business models and introduce new ones.
“We have to think about what that’s going to mean to our products and services as we move forward,” Bartlow says. Getting there required re-engineering Liberty’s software capabilities. Like most insurance companies, mainframes and monoliths drove their success over past decades. That approach worked in calmer times, but now Liberty is refocusing their software capability around innovation more than optimization. Liberty is using a stripped down set of three goals to make this urgency and vision tangible.
“The idea was to really change how we’re developing software. To make that real for people we identified these bold, audacious moves — or ‘BAMS,’” says Liberty Mutual’s John Heveran:
These BAMs grounded Liberty’s strategy, giving staff very tangible, if audacious, goals. With these in mind, staff could start thinking about how they’d achieve those goals. This kind of manifesto, makes strategy actionable.
So far, it’s working. “We’re just about cross the chasm on our DevOps and CI/CD journey,” says Liberty’s Miranda LeBlanc. “I can say that because we’re doing about 2,500 daily builds, with over a 1,000 production deployments per a day,” she adds. These numbers are tracers of putting a small batch process in place that’s used to improve the business. They now support around 10,000 internal users at Liberty and are better provisioned for the long ship ride into insurance’s future.
Choosing the right language is important for managing IT transformation. For example, most change leaders suggest dumping the term “agile.” At this point, near 25 years into “agile,” everyone feels like they’re agile experts. Whether that’s true is irrelevant. You’ll faceplam your way through transformation if you’re pitching switching to a methodology people believe they’ve long mastered.
It’s better to pick your own branding for this new methodology. If it works, steal the buzzwords du jour, from “cloud native,” DevOps, or serverless. Creating your own brand is even better. As we’ll discuss later, Allstate created a new name, CompoZed Labs, for its transformation effort. Using your own language and branding can help bring smug staff onboard and involved. “Oh, we’ve always done that, we just didn’t call it ‘agile,’” sticks-in-the-mud are fond of saying as they go off to update their Gantt charts.
Make sure people understand why they’re going through all this “digital transformation.” And make even more sure they know how to implement the vision and strategy, or, as you start thinking, our strategy.
“Communication is essential to employee engagement. We are all plugged in and on our phones; we are always looking for ways to connect with employees electronically. In the workplace, it is the face-to-face that matters the most. The communication between a leader, a manager, or a supervisor and their employees is the most effective.”
Nessing explains that it can be difficult for people who are unaccustomed to engagement.
“If you are speaking to a line crew in the field about something they are not familiar with, you have to find a way to communicate in language that they can relate to.”
Original source: Employee Engagement In The Digital Age
Lone wolves rarely succeed at transforming business models and behavior at large organizations. True to the halo effect, you’ll hear about successful lone wolves often. What you don’t hear about are all the lone wolves who limped off to die alone. Even CEOs and boards often find that change-by-mandate efforts fail. “Efforts that don’t have a powerful enough guiding coalition can make apparent progress for a while,” as Kotter summarizes, “But, sooner or later, the opposition gathers itself together and stops the change.”
Organizations get big by creating and sustaining a portfolio of revenue sources, likey over decades. While these revenue sources may transmogrify from cows to dogs, if frightened or backed into a corner, hale but mettlesome upstarts will are usually trampled by the status quo stampede. At the very least, they’re constantly protecting their neck from frothy, sharp-tooth jackals. You have to work with those cows and canines, often forming “committees.” Oh, and, you know, they might actually be helpful.
How you use this committee is situation. It might be the placate enemies who’d rather see you fail than succeed, looking to salvage corporate resources from the HMS Transformation’s wreak. The old maxim to keep your friends close and your enemies closer summarizes this tactic well. Getting your “enemies” committed to and involved in your project is an obvious, facile suggestion, but it’ll keep them at bay. You’ll need to remove my cynical tone from your committee and actually rely on them for strategic and tactical input, support in budgeting cycles, and, eventually, involvement in your change.
For example, a couple years back I was working with all the C-level executives at a large retailer. They’d come together to understand IT’s strategy to become a software defined business. Of course, IT could only go so far and needed the the actual lines of business to support and adopt that change. The IT executives explained how transforming to a cloud native organization would improve the company’s software capabilities in the morning. In the afternoon, they all started defining a new application focused on driving repeat business, using the very techniques discussed in the morning. This workshopping solidified IT’s relationship with key lines of business and started working transforming those businesses. It also kicked off real, actual work on the initiative. By seeing the benefits of the new approach in action, IT also won over the CFO who’d been the most skeptical.
As this anecdote illustrates, building an alliance often requires serving your new friends. IT typically has little power to drive change, especially after decades of positioning themselves as a service bureau instead of a core enabler of growth. As seen in the Duke lineworker case above, asking the business what they’d like changed is more effective than presuming to know. As that case also shows, a small batch process discovers what actually needs to happen despite the business’ initial theories. But, getting there requires a more of a “the customer is always right” approach on IT’s part.
Now, there are many tactics for managing this committee; as ever Kotter does an excellent job of cataloging them in Leading Change. In particular, you want to make sure the committee members remain engaged. Good executives can quickly smell a waste of time and will start sending junior staff if the wind of change smells stale (wouldn’t you do the same?). You need to manage their excitement, treating them as stakeholder and customers, not just collaborators. Luckily, most organizations I’ve spoken with find that cloud native technologies and methodologies so vastly improve their software capabilities, in such a short amount of time that winning over peers is easy. As one executive a year intro their digital transformation program told me, “holy-@$!!%!@-cow we are starting to accelerate. It’s getting hard to not overdo it. I have business partners lined up out the door.”