Software is blurring the line between tech and retail, new and old

The traditional story on digital transformation is that it’s about mainstream—or legacy—enterprises adopting the software- and user-experience-driven mindsets of technology companies such as Amazon and Netflix. However, we’re seeing that conventional wisdom evolve as more companies mature in their software capabilities.

In most circumstances, the traditional notion of digital transformation still rings true. Case in point: this Wall Street Journal profile of DICK’S Sporting Goods, a large retailer that has (thanks in part to its relationship with Pivotal) transformed its software-development culture and platforms. The shift resulted in a 17 percent jump in digital revenue during 2018, and predictions that DICK’S, which is looking to hire dozens more roles on its technology teams, will soon command 50 percent of the retail sporting goods market.

This is digital transformation 101. There might be some bumpy stretches along the road as the balance between physical and digital shifts, but in the end there is a more streamlined, agile and competitive business. Even technology companies such as Microsoft have had to deal with shifting revenues and margins as they transitioned from licensed-software to cloud-first companies, but emerged on the other side more valuable than ever.

Less common, but no less interesting, is when large, old, mainstream enterprises actually become technology leaders—and, in some cases, technology vendors. The big news this week is that McDonald’s paid more than $300 million to acquire an Israeli machine-learning-based personalization startup called Dynamic Yield. A lot of attention is being paid to McDonald’s stated goal of first using the technology to personalize and optimize drive-thru orders, but the story actually goes quite a bit deeper.

For starters, as the Wired article linked to above points out, McDonald’s can also use the Dynamic Yield acquisition to optimize any number of other parts of its business—from in-store and online orders, to how its kitchens operate. McDonald’s has a lot of data, and now it also has a team of skilled data scientists to help the company leverage all that info.

If you’re wondering why McDonald’s couldn’t just buy Dynamic Yield’s software, the company’s executive vice president and global CIO David Henry told WIRED, “It’s probably less about the product and more about the data scientists that come with it, the people that come with it, and their ability to move quickly with us.” (Read this article from The New Stack for good advice on nurturing existing technical talent within your company.)

Another interesting wrinkle: Dynamic Yield has an existing customer base of big-name retailers, and will continue to operate and serve them as an independent business. So a relatively small investment (for a company the size of McDonald’s) nets it talent, technology and an additional revenue stream. And as Dynamic Yield works with more companies, McDonald’s gains even more insight into how the customer experience is evolving and how it can take advantage of that for its core business of selling hamburgers.

On a related note, Pinterest has hired Walmart’s CTO as its new head of engineering. This might seem counterintuitive, until you consider the amount of effort Walmart has put into its own engineering prowess over the past several years (perhaps exemplified by Walmart Labs) in an attempt to fend off competition from Amazon. It’s also likely that as digital-first companies like Pinterest mature, they benefit from the knowledge of someone who has managed software targeting mainstream users under the pressure and responsibilities of public markets.

And as a reminder of why we all care so much about digital transformation in the first place, there’s Apple’s new credit card that does away with nearly everything we’ve come to associate with credit cards. It’s a shot across the bow at fintech and personal-banking companies, and a reminder that they don’t just have to compete against each other—Apple and other cash-rich tech companies can do just about anything they want.

Capex vs. opex is still a question

Survey shows enterprises are building new data centers (Data Center Knowledge): You have to consider the source (a data center trade group), but the clear desire of cloud providers to get into the hybrid-cloud space is evidence that data centers are here to stay.

Pinterest cut a deal with Amazon Web Services that requires it to spend $750 million with the cloud leader by 2023 (GeekWire): Is that cheaper than running its own data centers? Maybe, maybe not. But as we also saw from Airbnb recently, getting a really good deal in the cloud can require a big commitment.

Think about why you use containers

Containers are mostly just for large enterprises (Michael Coté): Some interesting findings from KeyBanc suggesting that many companies are cooling on containers, perhaps because containers (as broadly defined) aren’t what companies thought they’d be. 

Spend, wisely, on security

Global security spending to top $103 billion in 2019, says IDC (ZDNet): It’s understandable why companies are spending this much, but there are also ways to improve security posture that don’t require writing yet another check. A lot of those have to do with people and processes, including at the application level.

DXC Security exec: Yes, I'd have thought we'd spend more on certs and laptop kit for staff, too (The Register): Spending more on security won’t necessarily improve things, but taking an axe to the security is not a good look, either. Especially if the worst happens—and there have been some scary things this week, from ASUS updates (look it up) to more ransomware.

Our security recommendations will help you handle the worst of what 2019 throws at you (Forrester): Some good advice in this blog post, and probably more in the full report. What really stands out is the part about focusing on soft skills, such as communication.

Machine learning needs holistic thinking

Why data science teams need generalists, not specialists (Harvard Business Review): This is really solid advice from Stitch Fix chief algorithms officer Eric Colson, if you’re looking to build out a data science team. Data science is not software engineering.

Machines treating patients? It’s already happening (Time): A reminder that artificial intelligence can be beneficial —even in areas where it’s gotten a bad rap, like medicine—if we focus on what it’s actually good at and keep expectations realistic.

Skymind raises $11.5M to bring deep learning to more enterprises (TechCrunch): The most telling thing about Skymind is its focus on integrating with existing enterprise data systems. At enterprise scale, there’s no meaningful AI unless data architectures and processes are up to speed and accounted for.

What is going on in the world of data and analytics? (Gartner Blog Network): There are a lot of loosely connected thoughts in here, but one thing worth thinking about is the emergence of roles like chief data officer (and, perhaps, data science) at a time when many folks in the more-traditional analytics world are nearing retirement.


5 Actions to Strengthen Your Application Architecture Competency (Gartner; subscription required)

Assessing Kubernetes-based hybrid container management platforms (Gartner; subscription required)

The IT implications of the 2019 CIO Survey for I&O leaders (Gartner; subscription required)

Formulate a cloud strategy in the context of your overall strategy (Gartner; subscription required)

Effective enterprise collaboration grows your bottom line (Forrester; subscription required)

The new paradigm of retail (Forrester; subscription required)

6 things you need to know to safely run Kubernetes (Pivotal webinar) 

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