Today, data speed is key
to continuous innovation and the creation of superior customer experiences. If your data pipes are “clogged,” you’re in trouble.
This article originally appeared on Forbes.com as part of Delphix Founder & Chairman Jedidiah Yueh's ongoing column. See the original post here on September 11, 2019.
Hailed as the “queen of the internet,” every year Mary Meeker releases an annual report illuminating digital trends — a canonical read for Silicon Valley insiders. This year’s 333-slide presentation surveys e-commerce, education, immigration, health care and the continued rise of China.
With all that information, it’s easy to miss a key insight for companies — something that has already caused a critical shift in competitive advantage and will dictate business winners and losers for decades to come.
Historically, winning businesses used human-generated data to gain a critical advantage over competitors.
From the 1890s to the 1950s, IBM depended on the interaction among sales, engineers and customers for the product innovation that drove their skyrocketing revenues. In the 1980s, Chrysler used focus group research for its product development efforts.
And in the early digital era, companies like Intuit went all-in on customer testing. They would literally recruit people off the streets and time Quicken usage with a stopwatch. After every test, developers would take what they learned and improve the program.
A major shift occurred from the 1990s to the 2000s. Netscape launched the web browser in 1994. Amazon launched Amazon Web Services, later known as “the cloud,” in 2006. Apple launched the iPhone in 2007 and then the App Store in 2008.
These technologies let apps proliferate and reach users across the world in ever simpler and more intuitive embodiments, covering every use case imaginable. Today, we’re continuing to witness the disruptive power of the Internet, mobile and cloud in tandem.
It’s an equation that will continue to recode the world.
Today, companies like Amazon use real-time, digital information collected from the browsers and mobile phones of their customers to improve the shopping experience. It has vastly expanded their digital assets with more reviews, content, browsing options and recommendation features.
But how does it make sense of all the data — and get the right data to the right places in time to help customers make their buying decisions?
Need For Data Speed
Today, data speed is key to continuous innovation and the creation of superior customer experiences. If your data pipes are “clogged,” you’re in trouble.
Meeker argues that data plumbing meets the new imperatives of business and breaks it down into three parts: collect data, manage connections and optimize data.
Collecting data helps companies understand customers and optimize business processes. As you increase customer inputs with assets like reviews and feedback, you can improve digital products. This helps companies improve direct customer or subscriber relationships.
Once you have proper data collection in place, you need to properly manage connections. First, you’ll need to organize internal versus external connections. Think products like Slack for internal and Intercom for external. You’ll need to manage across multiple channels to interact with users — in apps, messaging, social media and old stalwarts like email. And you’ll need to integrate customer data across often-siloed IT systems, such as ERP, CRM, HCM and their SaaS counterparts.
Next, companies need to optimize data in order to improve analytics, recommend, and personalize the customer experience. And with all that data moving at speed, companies need to manage runaway data growth and eliminate systems and operational inefficiencies.
Clogged Data Pipes
The reality, in my experience, is that few companies have mastered data plumbing. Data is often both the most important tool in the arsenal and the biggest challenge.
Ensuring data flow is difficult for incumbents because data is growing in size, volume and complexity. It’s also distributed across data centers, co-location facilities, managed service providers, SaaS vendors and multiple public clouds — that's the new hybrid, multicloud reality.
In addition, data privacy, security and governance have all become board-level topics. With new data regulations like the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR), the regulatory environment for data evolves almost as fast as the competition.
Yet despite its importance, companies struggle with the basics of data. I’ll often ask executives at a company, who owns the data? Is it the chief data officer? The response is often, "No, they manage governance but do not own the data." Is it IT? "No, they own the systems that move and store data — networks and storage — but not the data itself." Application development? "No, they define the structure and usage of data in applications, but they don't own the data in the apps."
In most cases, there’s no one clearly responsible for data.
Rise (And Acquisition) Of The Data Plumber
It’s no wonder that so many vendors have emerged to solve different parts of the data plumbing problem.
And big tech companies have been paying close attention. In 2018, Salesforce bought MuleSoft at an enterprise value of $6.5 billion. This year Google acquired analytics startup Looker for $2.6 billion. And most recently, Salesforce acquired Tableau Software for $15.7 billion.
Survival Of The Data Fittest
But for the rest of the world’s companies, that can’t afford to acquire data plumbers, what is the key to data mastery? Companies need to ensure they have clear ownership, accountability and objectives when it comes to data.
I often find it takes Fortune 1000 companies months to move data from production applications to downstream needs like application development, user testing or AI experiments. Data movement, even for the biggest apps, should take minutes, not months.
Companies need to measure data plumbing metrics, set best-in-industry objectives and invest in modern processes and technologies. They need to assemble agile, self-sufficient teams around data, just as they did for software development. And they need to demand more impact — real revenue growth or material strategic contributions from their data investments.
As I’ve written before, companies are slowly waking up to the reality that every company is a data company — if they want to survive. And in this new, data-driven world, those with fast data will outrun (and eventually eat) the slow.