Chapter 14: Monday, November 10 – The Unicorn Project


• Monday, November 10

On Monday morning, Maxine is startled. The team has exceeded her expectations once again. They are all gathered in a conference room to quickly review status and talk about areas where they need help.

“Before we start, there’s something I think we need to do,” Maggie says. “We really need a code name for this effort. If we’re working toward something big, we need to have a name. The more we accomplish, the more we’re going to have to talk about what we’re doing, and we can’t keep referring to ourselves as the Rebellion.”

“What’s wrong with Promotions?” someone asks.

“Well, that’s the name of the team,” she responds. “But the team has changed so much since our friends from Data Hub have joined, and there are so many new initiatives we’ve started. I think we need a new name because the way we’re working is so different than before.”

The ideas start flying fast and furious. Serious names are proposed: Ulysses, Phaethon, Iliad … and names from the US space program: Mercury, Apollo, Gemini …

“They’re so serious, and they sound too much like Phoenix,” Shannon says. “I wouldn’t want anyone to think there’s any similarity between what we’re doing and the way the Phoenix Project turned out.”

“Totally,” Brent says. “It wouldn’t bother me at all if we salted the ground to make sure no program is ever named ‘Phoenix’ again.”

“How about from movies? Like Kill Bill, Blade Runner, Star Wars?” suggests Shannon. Others propose names of music bands, Pokémons, board games, weapons from Dungeons and Dragons …

“How about the Unicorn Project?” suggests Dwayne, obviously half-joking. “That’s pretty distinctive.”

Maxine laughs out loud. She loves it. The term “unicorn” is often used to reference high-flying tech startups and the FAANGs that Erik talked about—the Facebooks, Amazons, Apples, Netflixes, and Googles of the world. Parts Unlimited is a century-old horse, but they are out to prove that they can do everything the unicorns can, with the right culture, technical practices, and architectures to support them. In fact, what is a unicorn besides a horse with a horn and painted up with some fancy rainbow colors?

And in our case, Maxine thinks, our competition is not the FAANGs—it’s the other horses in our industry and tiny little software startups that are encroaching on our market. Startups have lots of ability to do things, she knows from personal experience, but they’re always lacking the resources to do them.

This is not a story about small beating large; it’s fast beats slow. What the past couple of months have decisively proven to her is that greatness can be stifled, but it can also be restored.

“I love it,” Maxine says. “Can you imagine Steve saying ‘unicorn’ during every Town Hall? Let’s do it.”

Everyone laughs. Dwayne says, “Umm, are you sure this will fly? Do we need to get approval for this?”

Maxine laughs out loud. “Approval? Since when do you feel like you need approvals from anyone? No, this is up to us. Yeah, the Unicorn Project,” Maxine tries it on for size. “Let’s do it.”

They decide that the Unicorn Project is the new name for the customized recommendation and promotion capabilities that, among many other things, will power the Black Friday and holiday promotion campaigns, and hopefully many more in the future. Orca is the name for the analytics and data science teams who will be working alongside and supporting the Unicorn promotion efforts. And Narwhal is the new database and API gateway platform that is being created that Unicorn will use. Unikitty is the name of the continuous integration and deployment platform being used by the Data Hub team, and some other carefully chosen teams in Phoenix.

Maxine is pleased. In hindsight, giving the team a unique name is probably long overdue. She’s always loved the Tuckman phases of teams, going through form, storm, norm, and perform. She’s ready to start norming and performing!

And team names help create an identity for the entire group, not just for individuals, and they reinforce the notion that team goals are more important than individual goals.

“You know, I’m also going to have say ‘unicorn’ in front of everybody,” grouses Maggie. But Maxine suspects that Maggie is secretly pleased.

Later that morning, Maxine is back in the auditorium for the bi-monthly Town Hall, her second since her exile, and the first since the disastrous release a month ago. She is especially interested to see how Steve will address that topic. Maggie told the team that she’ll be presenting one slide to the entire company about their hopes and aspirations for the Black Friday campaign.

Just like the last time, Maxine grabs a seat as close to the stage as possible. But this time, she’s surrounded by her teammates. Kurt is sitting in the row behind her, and she is excited to see Maggie backstage being wired up with a microphone.

At exactly nine, Steve comes on stage and welcomes everyone to his sixty-seventh Town Hall. He promises to talk about vision and mission, as well as annual goals. He says, “I also want to take some time to address all the problems associated with the Phoenix rollout and our hopes for the upcoming Black Friday campaigns.”

As he has in every previous Town Hall, he talks passionately about the Parts Unlimited mission to help hard-working customers keep their cars running so they can conduct their daily lives. After spending an entire weekend working with the in-store manager and new frontline staff, Maxine has gained a tremendous appreciation for how Steve’s relentless repetition of these organizational goals are reflected in the daily work of so many people at the company.

“Our business is one that depends on operational excellence and superb service. We make a simple promise to customers: that we will provide parts and services that help keep their cars running. When we released Phoenix into production, we let everyone down. We let our customers down, we let our employees down, and we let our investors down.

“We made promises to customers that we couldn’t keep. Merchandise we offered them wasn’t in stock or couldn’t be purchased, and we even accidentally disclosed hundreds of credit card numbers. We’ve given away millions of dollars in vouchers to customers we let down, but we can’t buy back the trust we lost.

“And it’s not just our customers. Many of our critical internal systems were down, preventing thousands of employees from doing their daily work. As CEO of the company, I take responsibility for this.

“I want to recognize everyone in this room who did absolutely everything they could to help fulfill our obligations to our customers. Many of you know that for the last two months, I’ve also been acting as the head of technology,” he says. “Don’t laugh, because as you know, I need a lot of help with anything technology-related. And I want to acknowledge all the amazing things that the technology teams did.

“Since then, I’ve been working with Chris Allers, VP of R&D, and Bill Palmer, VP of IT Operations, to do some radically different things. Among them was the thirty-day feature freeze. Everyone in technology worked on fixing problems and paying down technical debt.

“For those of you not in technology, ‘technical debt’ is what creates hardship, toil, and reduces the agility of our software engineers,” he continues. “It’s like a spreadsheet that’s grown over years to the point that you can’t change it anymore without breaking formulas or introducing errors. But technical debt affects us at a much vaster scale, involving systems that run the most complex processes in the company.

“I’ve been hearing from people across the organization that this was badly needed,” he says. “Just like in manufacturing, where I come from, it’s important to have a sustainable work pace and to limit our work in process to make sure that work keeps moving through the plant. And that’s what we’re doing here.

“This quarter is make or break. We promised the world that we’d get Phoenix out in September, but because of all the features we delayed, we’re not getting the sales benefits that we hoped for. Now we’re well into the quarter, with the holiday buying season right ahead of us. We are out of time.

“Here to talk about what we’ve learned is Maggie Lee, our senior director of retail product marketing,” he says. “Come on out, Maggie.”

Maggie looks as nervous as Maxine has ever seen her, but most people would never notice. Maggie says, “As you know, Phoenix has always been about helping customers buy high-quality parts they need from us faster, easier, and cheaper. Over the years, we’ve built the groundwork to make that happen, but we haven’t been able to activate those capabilities … yet.

“Thanks to Steve, Chris, and Bill, I’ve had the privilege of working with a team made up of a cross-section of the entire company, including Finance and Accounting, Marketing, Promotions, Retail Operations, and of course, an incredible technology group to figure out how we can deliver a small but extremely important set of Phoenix goals. We want to generate great customer recommendations and enable the Promotions team to sell profitable products that we have in inventory,” she says. “We have years of customer purchasing data, and because of our branded credit cards, we know our customer demographics and preferences. If we can get those promotions to the customer, we think we can make a real difference to the company and create incredible value for our customers.

“And that’s why I’m excited to introduce the Unicorn Project,” she says, smiling as everyone in the audience laughs at the whimsical name. “I’d like to recognize Kurt Reznick and Maxine Chambers who approached me a short time ago with a radical idea to make this happen, along with a group of engineers who wanted to help. We have all been working with the support of the entire Phoenix Project, toward the goal of having incredibly effective campaigns in support of Black Friday, one of the highest selling seasons of the year. Our goal is to break all the records and make it the top selling day in company history.”

Maggie continues, “We will be conducting a series of tests over the next two weeks to ensure that things go right when we launch the campaign to millions of customers on Black Friday,” she says. “Thank you and wish us luck,” Maggie smiles, waving to everyone and shaking Steve’s hand before exiting the stage.

“Thank you, Maggie,” he says. “There are some who say this won’t work, including some people who championed the Phoenix Project for many years. But Maggie and her team have made me a believer. In my career, I’ve found that whenever you have a team of people who are passionately committed to achieving a mission and who have the right skills and abilities, it’s dangerous to bet against them, because they’ll move heaven and earth to make it happen. So … good luck to the Unicorn Project!”

Maxine cheers and whistles loudly. She also notes Steve’s oblique reference to Sarah and her absence today. She looks around and confirms that she is nowhere to be seen, wondering whether that’s good news or bad news.

For the next couple days, the team is entirely focused on the work required to generate winning promotions by Black Friday. Everyone is buried with urgent work. Maxine again brings up with Kurt the need for more experienced people to help.

“I’m way ahead of you,” he says. “I got Chris to bring in William from his leave of absence and I’m bringing him over to help the Unikitty team.”

“No way,” Maxine says, incredulous. She laughs, thinking about how Chris probably reacted. “How’d you manage to get him back from his indefinite leave of absence?”

Kurt laughs. “Let’s just say I called in every favor built up over years of doing good. I had them all lobby Chris to bring back William. There’s no better person to help us get these environments working. It also feels great that he’s back from his unjust exile.”

Maxine heartily agrees and is again impressed with Kurt’s ability to deliver the things that the teams need, able to navigate the organization in a way very different than the official org chart would suggest.

Meanwhile, the Narwhal team is trying to figure out a workable API gateway and database solution given all the things the various teams need. The stakes are very high. The amount of data they’ll be dealing with is huge, and the consequences of it not working would be disastrous.

This is an ambitious undertaking, but one that dazzles Maxine. Narwhal will shield everyone from almost all the API problems that Cranky Dave had complained so much about, often without any need to change the back-end systems. It will serve as a central place where developers can easily access the data they need and easily find other company data that might be able to help solve their business problems, often from distant silos. And Shannon has been helping ensure that Narwhal will keep all this data secure, enforcing policies around authentication and PII anonymization.

A major part of Narwhal is that it will often store copies of the major company systems of record—anytime that the back-end systems are too slow, too difficult to change, or too expensive to actually conduct all the transactions they need.

“We’ve got to make a decision,” Dwayne says in a big meeting that he pulls together late Wednesday afternoon. To Maxine he says, “Believe it or not, all of us are strongly in favor of a pure NoSQL solution. We think it’s the fastest way to get all the data we need into a place that we control and satisfy the performance needs of the Unicorn team.

“Brent and the team have two NoSQL clusters running, one for Test and one that we could use for Production,” Dwayne says. “And data ETL process … uhh extract, transform, and load … is going better than we thought. We have an extended team cobbling together a bunch of technologies to copy data from nearly twenty different systems of record into our database, using a combination of commercial and homegrown tools. The good news is that it’s going faster and more quickly than we thought …

“But here’s our conundrum,” he says. “We were planning to keep all the data in both NoSQL and MySQL databases, just in case the NoSQL option blows up. But after the ETL experiences and some large-scale tests, we think we should ‘burn the ships’ and go pure NoSQL. Supporting two back-end databases is going to slow us down, and we won’t get any of the productivity advantages we were aiming for.”

“Whoa,” she says, surprised. This was a much more daring approach than Maxine expected. In fact, it was probably decisions like this that caused people to create the TEP-LARB.

No one in the company had used NoSQL in production in a significant way, let alone for something so large and mission-critical. Usually Maxine thinks prudence and practicality would disqualify such a risky approach for such a high-stakes project, especially when there’s so little time to research and gain real-world production experience. She says as much to the team.

“Normally I’d agree, Maxine. You’d think the biggest risk would be operational,” Brent says, seeing her concerned expression. “But I think the far bigger risk is losing relational integrity between all these tables that we’re copying from everywhere in the enterprise. As you know, a NoSQL database won’t enforce relational integrity like most databases we’re used to. But I’m comfortable that we can enforce it at the API level.”

Although nerve-wracking, Maxine admits that it is exciting to see technologists at the top of their game working to solve an urgent business problem. Maxine asks a bunch of questions, sometimes repeatedly, and scrutinizes their thinking. But by the end, they’ve all convinced each other to go all-in on NoSQL.

“Okay, let’s burn the ships,” Maxine finally says. There’s just no time for any other option. She does not like this level of uncertainty, but she trusts the team.

The developer agility this will enable is undeniable, but more than ever, Maxine realizes how engineering constrained they were. To work with more systems, they really needed a bigger team. She reminds herself that this again will be the first topic to discuss in her next meeting with Kurt.

Over the next two days, the teams work on their portions of the Unicorn Project. Maxine spends most of her time on what she views as the riskiest part of the whole operation, which is getting all the data into the Narwhal NoSQL databases and enabling all the teams to be able to access what they need. She knows that they are now well past the point of no return, having torched the ships they knew how to sail.

The most difficult part was not the mechanics of importing the data from twenty different business systems. Instead, it was trying to create a unified vocabulary and taxonomy that they could use, because almost every business system had different names for similar things.

Physical stores have five different definitions of in-store sales, including from a company acquired decades ago. There are six different ways that products are catalogued. Product categories and prices don’t line up. The business rules around pricing and promotion are exercises in forensic archaeology. They pulled in business analysts from across the company to help make sense of it and make decisions about how they should be represented.

Maxine found herself constantly switching between insisting on clarity and consistency to ensure accuracy to saying “good enough for now” and deferring decisions that would require days of consensus-building because they would impact Parts Unlimited for decades to come. Without her extensive experience working with enterprise systems, she’s sure she wouldn’t have had the judgement necessary to make these types of calls, especially given the deadlines involved.

Everyone is focused on the big, upcoming Demo Day, where each team will show their portions of the system on the final days before Black Friday. Maggie will be leading it, and almost all the stakeholders will be there, as well as all the technology executives, ending with a final “go/no go” launch decision.

Because of the high stakes involved, Maxine makes sure that she attends all of the daily engineering team standups, where team members quickly share progress and, more importantly, what help they need. She approves of how quickly and efficiently these meetings are run, with blockers being urgently handled by the team leads.

On this tight timeline, every day counts. Thanksgiving is just over a week away. She listens intently as she sits in the Unicorn standup. One of the two most senior data scientists from the Promotions team is visibly flustered. “We still don’t have the fields we need in the one percent subset of the customer list from the Data Warehouse team, and we still can’t match up nearly half of the physical store order data.

“And for our data analysis, the Narwhal database is incredibly fast, compared to what we’re used to. But because of all the joins we need to do, the query times are still orders of magnitude too slow,” he continues. “Given the deadlines, we only have one or two shots at this, and if the results are like the ones we’re getting right now, we will not be ready for the Black Friday launch. And if we use the data we have right now, the promotions are guaranteed to be a real dud. Just this morning I found a case where we would have sent offers for snow tires to people in Texas.”

Oh, shit, thinks Maxine. This is what you get for waiting too long to invite the data scientists to the engineering meetings. She says out loud, “Okay, I’ll pull together an emergency single-topic meeting later this morning. I’ll make sure Kurt and Maggie are there, as well as the Narwhal team. Could you prepare a ten-minute briefing about these problems and some ideas on how to solve them?”

When he nods, Maxine takes out her phone and calls Kurt.

Two hours later, everyone is gathered in a conference room listening to the problems that the Analytics and Promotions teams are having. After fifteen minutes, Maxine is feeling genuinely daunted at the sheer scale of the problem.

It’s no wonder the Analytics team has made so little progress—what they want to do is simply impossible with the infrastructure they’ve built. The data sets are orders of magnitude larger than what they can handle. Maxine immediately sees that the queries the data scientists are building are a complete mismatch to what they’ve built Narwhal for. Narwhal is stellar at handling API requests from all the various teams across the company, but now they’re learning that it’s spectacularly not great for what the Analytics teams need to do.

Worse, the Unicorn teams still can’t get the data they need. It takes the Data Warehouse team four months to get twenty lines of SQL from Dev to QA to Production. And every time they do, reports break or show incorrect data. Apparently last month, a schema change somewhere broke almost every report in the company. To Maxine, it’s the same problems they had with the Phoenix Project, but instead of code, it’s for the data that the Unicorn teams need.

Moreover, the Data Warehouse teams still haven’t reconciled the different definitions of product, inventory, and customer from the physical stores and e-commerce stores. The newly created Narwhal teams were already way ahead of them.

Maxine drums her fingers. She cannot believe that they’ve run smack into another Phoenix-scale bureaucratic quagmire—the Data Warehouse is sitting on so many things they need.

As people continue talking, Maxine stares at the numbers on the whiteboard. This is not going to work, she thinks. She decides that she needs to discretely signal Kurt to step out into the hallway so she can tell him that there’s just no way that the Promotions plan can realistically work as currently envisioned. They’ll need to convince the Unicorn team to drastically scale down their plans. Or maybe the Rebellion should abandon them and find another program to work with to generate a business win.

In order for the Unicorn team to succeed, they somehow need to be decoupled and liberated from the giant data warehouse, and maybe even Narwhal, to support the massive calculations and queries they need to do.

“I know what you’re thinking,” Shannon says, just as Maxine is about to get Kurt’s attention. “This looks impossible, right? But I spent nearly five years on the Data Warehouse team thinking about this. Let me show you something I’ve wanted to do for years.”

Over the course of the next thirty minutes, Shannon presents a breathtaking plan that she’s obviously been thinking about and studying deeply. She is proposing to build a Spark-like big data and compute platform, fed by an entirely new event-streaming bus, modeled closely to what the tech giants all have built to solve their data problems at scale. It would allow hundreds, even thousands, of CPU cores to be thrown at the computations, allowing analyses that currently take days or weeks to be done in minutes or hours.

Maxine is familiar with these techniques. Their use exploded after the famous 2004 Google Map/Reduce research paper was published, which described the techniques Google used to massively parallelize the indexing of the entire internet on commodity hardware, using techniques at the core of functional programming. This led to the invention of Hadoop, Spark, Beam, and so many other exciting technologies that transformed this space, just like NoSQL revolutionized the database landscape.

Shannon describes how this new data platform would be fed by a new event streaming technology. “Unlike Data Hub, where almost every business rule change also requires a change from the Data Hub team, this new scheme would allow a massive decoupling of services and data. It would enable developers to change things independently, without needing a centralized team to write intermediary code. And unlike the centralized Data Warehouse, the responsibility for cleaning, ingesting, analyzing, and publishing accurate data to the rest of the organization would be pushed into each business and application team, where they have the most knowledge of what the data actually means.”

She continues, “The importance and urgency of keeping this data secure, making sure that we don’t store PII that we shouldn’t, the need to encrypt it at rest, and the risks of what could happen to Parts Unlimited if this data were stolen are tantamount.” It’s obvious that Shannon is passionate about how this platform must ensure the security of all this data, not leaving it to each individual team.

And most appealing to Maxine, it could also support an immutable event sourcing data model, which would be a massive simplification compared to the current morass of complexity built up over decades.

It was also fast. It would have to be, because Data Hub and potentially every application in the enterprise would eventually be throwing everything into this new message bus: all customer orders, all customer activity from their CRM, everything from their e-commerce site and marketing campaign management systems, all customer activity from their in-store and garages … all of it.

When Shannon is done presenting and has answered questions from the team, Kurt looks pale. “You’re kidding me. We don’t even have approval to get Narwhal off the ground yet. And adding all of … this … would quadruple our compute and storage footprint … and potentially put even more sensitive data out in the cloud,” he says, gesturing at the whiteboard. “Oh, man, Chris is going to lose his shit. There is no way he’ll go for this.”

Even Brent looks slightly ill. “I’ve always wanted to run something like this, but … it’s just so much new infrastructure to build at once. This seems a bit reckless, even to me.”

Maxine studies Kurt’s expression, and then Shannon and her drawings that cover two full whiteboards. Then she laughs, momentarily enjoying Kurt and Brent’s discomfort. But she knows how they feel. Gamblers who lost everything at the casino probably had moments of reflection and prudence like this before they went all-in.

She says, “Are we playing to win and to establish the technical supremacy we need to keep up with what the business needs, or do we just keep limping along, shackled to things built decades ago, and tell our business leadership to throw in the towel and stop having good ideas?”

Maxine thinks Shannon’s idea is a good one, even though it seems suicidal. Maxine says, “All my intuition and experience says that our data architecture has created another bottleneck that affects every area of the company. This is a problem that’s far bigger than just developers. Anyone who needs data as part of their daily work isn’t getting what they need.”

“Yes,” Maggie says, looking like she’s been hit by a bat. “That’s absolutely right! I’ve got twenty-five data scientists and analysts across five teams who never have the data they need. But it’s not just them—almost everyone in Marketing accesses or manipulates data. Operations is mostly about data. Sales operations and management is all about data. In fact, I’d bet half of all Parts Unlimited employees access or manipulate data every day. And for years, we’ve been handcuffed by the way everything has to go through the Data Warehouse team.

“And frankly, we need pros like you to help,” she says, embarrassed. “We have a few data visualization platforms that we manage internally, but we’re not software people. In fact, earlier this year we managed to corrupt all our order data when the vendor told us to change the server time zone.”

Brent groans, and Maxine is relieved that he manages to refrain from saying anything demeaning about the vendor or Maggie’s server administrators.

Seeing Kurt’s sudden expression of rapt interest and calculation, Maxine smiles. She knows that hearing this sort of distress and suffering is exactly what motivates him into action. She says, “Let’s start small, with the most critical capabilities to enable the Unicorn team. We leverage all the ETL work we’re already doing with Narwhal, and we use fully managed and battle-tested data platform services in the cloud that could reduce a lot of the operational risk. Here’s what I’m thinking …”

Maxine congratulates herself that over the next four hours, no one leaves the room. Or quits. Instead, they wrangle over the whiteboard and come up with an outline of a plan that everyone tentatively agrees to explore. They defer the event streaming platform, but Maxine and Shannon will lead the creation of something that can provide more bulletproof data transformations, get things under version control, build automated testing to confirm the correct shape and size of data before it’s ingested, and so many other things to prevent all these data accidents she’s seen and heard about.

Kurt and Maggie promise to start the delicate discussion with Chris and Bill to head off a political battle with the Data Warehouse team, who might feel threatened. Which is not unreasonable, thinks Maxine. The Data Warehouse team has been the custodian of this data for decades, and now we’d be liberating it, making it available to anyone who wants it, on demand, without opening a ticket.

Despite all these plans, everyone knows that there is a real chance of total failure. She hears Brent mutter from the whiteboard, “I love it, but there’s just no way we can get all of this done by Thanksgiving …”

As Maxine’s teenagers would say, Brent is not wrong. But clearly, the way they’re doing data now is not working, and here’s an opportunity to show that there’s a better way. If there’s any time that deserves courage and relentless optimism, it’s now, she thinks.

When Brent finally says, “Let’s call this Project Panther,” Maxine knows that there’s a shot of making this all work.

On the night before Demo Day, many teams work late into the evening. The next morning, everyone is there as the Black Friday Promotion demos begin in the lunchroom. Kurt asks Maggie to kick off the session to help frame the “why” behind all of their efforts, but everyone knows that Black Friday is just days away. Everyone working on the Unicorn Project knows that it’s not an exaggeration that the survival of the company depends on their efforts.

The Unicorn Project is now high-profile. And Maxine knows that if things don’t go well today, it will not be good for the company, and it will be very not good for Maggie, Kurt, and herself.

Maggie begins, “As everyone knows, Black Friday is right around the corner. Our goal is for the Unicorn Project to drive real revenue, made possible by the Orca, Narwhal, Panther, and mobile app teams. Our focus is on using inventory information and personalization data to drive promotion and to get useful information into our apps, such as inventory availability. Specific outcomes we want to affect are revenue, repeat engagement in our mobile apps and e-commerce site, and campaigns that generate a positive response.”

Maggie pauses. “And we have a special guest in the room, Bill Palmer, our VP of IT Operations, who helped create Project Inversion, which allowed us to focus so much energy on the Promotions effort. We also have a big contingent from Ops here who are helping fast-track all these initiatives. First up is Justine to present for the Orca team.”

“I’m Justine, and I’m on the team responsible for generating the data used to create the promotions. As Maggie mentioned, our goal is to give Marketing the ability to create the best promotions based on everything we know about our customers.

“Data is the lifeblood of the company,” she continues. “In Marketing, almost all of us access or manipulate data to guide the efforts of the company. For the first time, thanks to the Panther platform that Shannon and team created, we can finally get the data we need, trust that it’s correct, and use all sorts of statistical techniques and even things like machine learning to predict what our customers might need. This is what we use to craft offers and promotions. I have no doubt that the future of the organization will be built upon understanding our customers and providing them what they need … and we are best able to do that by understanding this data.”

Shannon smiles as Justine goes on to outline Orca’s successes. “Over the last two weeks, our goal was to get all the queries needed to support the top priority use cases: we need to find out what the top-selling items are, which customer segments have purchased them, and vice versa. For each customer segment, we need to determine the products they buy most frequently.

“A great promotion is one where we can sell inventory we already have, but also at the optimum price. We don’t want to unknowingly sell products lower than what customers are willing to pay. And we can only learn what that price is through experimentation,” she says.

“We built a simple web application where everyone can generate and run these queries, build candidate promotions, and share them with each other,” she continues. “On the screen, you’ll see all the top-selling items along with their photos. This is pretty great but also boring, and it’s very difficult to quickly understand what all these SKUs actually are. We realized that the e-commerce site has images for all these products. So we asked Maxine and the Narwhal team if they could give us those links too, which they did within hours and without needing to open a ticket! By the end of day, with only ten lines of code, we were showing these images in our app, which helped everyone on the team generate more compelling offers more quickly and effectively. That’s been a crowd pleaser,” she says with a smile.

Maxine sees Tom, her former Data Hub coding partner, join Justine at the front of the room. He says, “Once we understood what the Promotions team was trying to do, generating this app was easy. The Narwhal people gave us the API, and we just used one of the modern web frameworks to display it. Justine is absolutely right about how awesome the Narwhal database API is. And it’s blazingly fast. I’m used to queries that take minutes or hours to run on big servers. So, hats off to the Narwhal team—I’m blown away. We couldn’t have done it without them.”

Maxine grins and sees that Brent and Dwayne also have huge smiles on their faces.

Justine shows her last slide. “We’re working with the Marketing teams to finalize the promotion campaigns for the two highest-priority customer personas: the Meticulous Maintainers and the Catastrophic Late Maintainers. For each of those, using the Panther data and compute clusters, we’ve generated candidate-recommended products and recommended bundles, which they’re still reviewing and tweaking. Once they’re done, we’ll help get those loaded into the product and pricing databases so we can execute the campaign.”

Unprompted, one of the senior Marketing people walks to the front of the room and says, “I want to acknowledge and thank everyone’s hard work. This is incredibly exciting and impressive. I’ve been amazed at how much this team has done in a couple of weeks. We’ve been at this for almost two years, but I’ve never been as excited as now. We’re taking all the data from the Orca team and fine-tuning the offers that we’ll be presenting throughout the Thanksgiving weekend. I think there’s millions of dollars of revenue that we can unlock!”

Maggie thanks him and Justine, applauding with the crowd. She then calls up Mark, the lead developer for the Parts Unlimited mobile app. He’s a tall man in his mid-thirties. His laptop is so covered in stickers of technologies and vendors that you can’t even tell what kind of laptop it is. “Good morning, and I’d like to just answer the question that you’re probably thinking. The answer is, yes, we’re the team that built the current mobile apps—both of them. We’re not proud, and we’re just glad users can’t rate an app with zero stars.”

People laugh. The Parts Unlimited app has been an embarrassment for years. “There’s so much we wanted to fix, but we were all put on other projects, so until recently, there’s been no full-time developers on the mobile apps. But as Maggie said, that has changed. Mobile is how our customers want to interact with us, so we’ve reconstituted the team, with a persona-driven approach that focuses on what our customers want,” he continues. “We’ve been working closely with the product owners to generate some quick wins and taking full advantage of what the Narwhal team has done.

“We’ve never had access to a store’s inventory levels before. We loved the idea of showing which stores nearest to the customer have a particular part in stock. We can use the geolocation data from the customer’s device, or they can have them put in a US zip code. Here’s what the page looks like now …”

He brings up an iPhone simulator and the Parts Unlimited app on the screen. “Getting inventory information from Narwhal was incredibly easy. So, when we click into the product page, you can see the item availability for all the stores around them. They can now reserve the item, so it’ll be guaranteed to be there for them to pick up, which again was made entirely possible by Narwhal. And now, we’re collecting information on how parts availability affects purchasing so we can compute how much of an effect this has.”

Wow. Maxine is impressed. She hasn’t seen any of this work before, and she loves what they’ve created.

And even though Mark had apologized about the app, Maxine thinks it looks really good. She’s always amazed by how great most mobile applications can look, presenting an incredibly rich amount of information—even the Parts Unlimited app. She’s used to engineering prototypes that she and other developers build, which look more like 1990s-era websites. It’s clear that the mobile app team had professional designers working on it. This polish is something that consumers now demand. If an app looks shabby, they’ll likely won’t use it, let alone open it a second time.

“All these changes have already been pushed out to the app stores. All we need to do to enable it for customers is flip a switch,” he says. “We’re also logging a ton more data back to Narwhal to help the Marketing teams perform experiments. We’re especially interested in what exactly should and shouldn’t be presented to the user in the search results and on the product pages to increase conversion rates. Narwhal performance is awesome—none of it slows down the user experience.”

He continues, “We’ve done hundreds of iterations internally, and we’re ready to use all the user telemetry to perform experiments with real customers. We’ve never been able to do anything like this before. This has been a fantastic experience for me and my team. Keep up the great work!”

Maggie thanks Mark and everyone claps in appreciation, then she turns to address the room again. “You’ve just seen demos of the progress we’re making. All these give us confidence that we’ll be able to execute some very exciting Thanksgiving promotions.

“We spent the month trying to come up with the best promotions, slicing and dicing the data in many different ways,” she continues. “We were able to spin up a bunch of compute resources in the cloud to do the necessary computations. We start the recommendations reporting run every evening and spin up hundreds of compute instances until we’re done, and then we turn them off. We’ve been doing this for the past four days, and it’s working well—really well. Right, Brent? Right, Shannon?”

Brent and Shannon are sitting at the front of the room, and they are beaming. Maxine is delighted that Brent, in particular, is so invested in the outcome. She’s never seen him so happy and having so much fun, which makes her thinks of the Second Ideal. And Shannon is rightly proud of getting Panther off the ground. There is absolutely no way that the teams could have generated these promotions without this new platform.

Panther was already making a huge difference in how teams worked with data. Errors in data uploads were being caught right away through automated tests. The teams could easily access any data from across the organization, and easily add new data, contributing to the entire collective knowledge that could be tapped to experiment and try out new ideas. It’s enabled scores of new reports and analyses to be conducted, leveraging an incredible variety of tools, many that Maxine has never heard of.

And to Maxine’s amazement, even the output of these discoveries and experiments are making it back into the Panther data platform, further enriching the data already there. Seeing and spreading learnings, as per Erik’s Third Ideal, Improvement of Daily Work.

Maggie shows a slide with a bunch of products on it. “These are the Unicorn promotions generated for my customer account. As you can see, it’s looked at my buying history and is letting me know that snow tires and batteries are fifteen percent off. I actually went to our website and purchased both because I need them. The company just made money because those are all items that we have excess inventory of and that have high profit margins.

“And here are the Unicorn promotions for Wes,” she continues, going to the next slide with a smile. “Looks like you got a discount on racing brake pads and fuel additives. That of any interest to you?”

“Not bad,” hollers out Wes.

“Given the incredible success of these initial experiments, here’s my proposal,” Maggie says. “As planned, I’d like to do an email campaign to one percent of our customers to see what happens. If everything goes well, we’ll go full blast on Black Friday.”

Maggie looks at the Ops leadership. “Sounds like a great plan,” Bill says. “Wes, is there any reason why we shouldn’t do this?”

From the front of the room, Wes says, “From an Ops perspective, I can’t think of any. All the hard work has already been done. If Chris, William, and Marketing have confidence that the code is working, I say go for it.”

Maggie cheers and says, “Everyone, we have a plan. Let’s make it happen!”

Maxine is cheering, along with everyone else. Suddenly curious, she looks around—again, Sarah is nowhere to be seen. You’d think she’d want to be here at a time like this, if anything to take all the credit. Her absence is conspicuous. And it makes Maxine nervous.