Every few weeks, we share insights with our Fuse subscribers along with news and trends we’re following across the web, including book recommendations.
Here’s a compilation of some of our key insights from last six weeks.
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Data is the Holy Grail
In the classic film Monty Python and the Holy Grail, viewers hear King Arthur and his trusty servant Patsy approaching with a trademark “clip-clop, clip-clop” sound. When the duo emerges from the primordial mist, you see (spoiler alert) that the source of all this noise is not, as might be supposed, a horse. Rather, Patsy is banging two coconut shells together as the king trots about on his own two legs. The duo is getting from point A to point B in their quest, but not in the most efficient or effective way possible.
Many companies follow that script.
Equipped with buzzword mandates like process optimization and data-driven decision making, it’s all too easy to make small adjustments that sound like you’re headed in the right direction but aren’t necessarily getting you there any faster.
How do you drop the coconuts and get on the horse (metaphorically speaking)? What does it look like to use data to drive optimization in real terms? We’ve got our eye on digital twins.
Before you run away (how’s that for a deep cut Monty Python reference?) from yet another data buzzword, it’s worth another look at this practical application of machine learning and data analytics.
Digital twins are most often used to optimize physical assets and processes like manufacturing, warehousing, and logistics. Using sensors to collect data on a product, machine, or physical process, the digital twin feeds real-time data to a machine learning algorithm to test variables and scenarios faster — ultimately leading to actionable process improvement insights.
These days, we’re starting to see more businesses use digital twin frameworks to optimize and innovate non-physical business processes like accounting, HR, and marketing as well. A digital twin simulation can help you surface interdependencies and inefficiencies that might otherwise be blind spots, especially if they’re baked into your business culture as “the way we’ve always done it.”
In the quest for digital transformation, don’t settle for coconuts. Instead, let’s talk about the ways your data can carry more of the weight for you.
Get smart: If all this talk of Monty Python and the Holy Grail puts you in the mood for an old-school movie night, good news: it’s available on Netflix. And if you’re looking for a more literary scratch for your Middle Ages (ish) itch, we’re reading Cathedral by Ben Hopkins. It’s a fascinating look at the complex processes involved in constructing architectural marvels in the days before edge computing. We may handle optimization differently now, but human nature stays the same.
A horse is a horse, and other martech myths
Martech is a crowded field, and a lot of the voices weighing in on your options have a horse in the race.* No one is out to skew the odds on purpose, but your organization is unique. Just because one solution is a front-runner doesn’t necessarily mean it’s a great fit for your business.
So how do you sort the facts from the hype and decide where to place your bets? We rounded up a few martech myths as a starting point.
Myth: One CDP is as good as another.
Fact Check: Finding the right CDP (or CRM, or DMP, or any other solution you can think of) isn’t a simple box to check. And, once you make your decision, integrating and customizing your platform will also take time and attention.
Myth: Everyone needs a CDP.
Fact Check: Depending on your use cases, you might be able to do everything you need to do within your current tech stack.
Myth: You should pick a platform and go all in.
Fact Check: It probably goes without saying, but when it comes to technology there are no one-size-fits-all solutions. One product might be a great fit for your needs, but that doesn’t mean that vendor should supply your entire tech stack.
Myth: Data and tech silos are just the way business works.
Fact Check: Regardless of size, scope, or industry, today’s businesses can’t afford to be siloed. When you’re evaluating a tech solution or rethinking your entire customer data strategy, prioritizing integration is always a safe bet.
On your mark.
Ready to put your martech through the paces? Read on to find resources to help you optimize your stack and get your customer data strategy across the finish line.
*Full disclosure: one of our team members won $100 when Rich Strike won the Kentucky Derby, but for the most part we are platform- and livestock-agnostic.
Get Smart: We try not to be too on the nose with our book recommendations but couldn’t help ourselves this time. In Data Strategy, Bernard Marr collects a solid primer on the data landscape and how your organization can use it (legally and ethically) to advance your goals. Spoiler alert, though probably not surprising given the title, strategy turns out to be the foundational driver for effective data use. Whether you read the book, our Ultimate Guide to Customer Data Strategy, or just want to get a sense of potential next steps, we’d love to chat about customer data. Grab a time that works for you.
Three technology strategies walk into a bar
If you’ve got a monolithic legacy system on your hands, sticking with the status quo isn’t a fun choice. But going nuclear and building back from scratch probably isn’t realistic. Wouldn’t it be great to find a middle ground?
Meet the composable enterprise.
It’s an iterative path toward digital transformation, with applications repackaged into components that can be used to build new solutions across the business. Piece by modular piece, you rebuild your technology ecosystem — becoming more efficient, effective, and scalable as you go.
As the glue that holds those components together, APIs are key to building a composable business. And developing secure API solutions that accommodate shifting capacity demands and amplify your technology takes a hefty dose of strategy and expertise. That’s what we love about it!
If APIs are your jam, too, or if you’re wondering if a composable system makes sense for your business, let’s talk. We’re talking APIs over IPAs in Cincinnati on June 16 and you’re invited. It’ll be fun!
Get smart: You’ve probably spent the day wondering how speculative/sci-fi/literary fiction relates to API strategy and microservices (or maybe that’s just us). But, we’d guess, the same type of mind that enjoys transforming legacy monoliths into composable enterprises would also really track with a book like How High We Go in the Dark by Sequoia Nagamatsu. Modular pieces linked together by strong bonds leading to an intricate and ever-expanding whole? We’re here for it (the book and the technology strategy).