In this special guest feature, Dan O’Connell, Chief Strategy Officer and a board member at Dialpad, takes a look at what will happen to organizations as they roll out real-time data capabilities this year– they’ll discover new ways to scale faster, fresh ideas to improve operations, and novel ways to reduce friction. Previously, Dan was the CEO of TalkIQ, a real-time speech recognition and natural language processing start-up that Dialpad acquired in May of 2018. Prior to TalkIQ, he held various sales leadership positions at AdRoll and Google.
Most of your data is worthless.
Okay, perhaps it’s not worthless—but it’s nowhere near as valuable as it used to be. The COVID-19 pandemic upended consumer trends and working habits. It changed the way we shop, socialize, work, and relax. Much of our existing data is representative of our pre-pandemic lives. Take seasonal demand. Are people going to flock to restaurants over the festive period? The truth is that we don’t know.
To thrive in the murky waters of post-pandemic life, organizations must harness real-time data that’s forward-looking and predictive. But that’s easier said than done.
Collect, analyze, and report—slowly
Until very recently, organizations had predominantly backward-looking data. Take customer satisfaction. If you wanted to know whether your customers were happy, you’d send out an NPS survey or tack some CSAT questions onto your customer service scripts. Results would trickle into a database. At the end of the month, someone would crunch the numbers and report on performance. All of that took time. It wasn’t uncommon to receive April’s numbers in mid-May.
It’s the same story in other disciplines. You gathered financial, productivity, or engagement data through the month, analyzed it, and reported on it later.
Because data was backward-looking, you were stuck in a reactive cycle. The data said sales are slipping in the midwest? Let’s up your marketing. Employee engagement is down in the Chicago office? Let’s interview your managers to see what’s up. You were always playing defense, never offense. Worse, you were chasing after the ball. You could never get in front of challenges or opportunities.
These challenges aren’t exactly surprising. Executives understood the limitations of historical data. If you could have given them instant access to reliable, real-time data, they’d have bitten your hand off. But the technology just wasn’t there.
Accessibility was always a problem. Data lived in old, siloed on-premise systems. Occasionally, for things like satisfaction surveys, you even had to deal with analog records. And when you finally got access to data, you had to work out what to do with it. While data warehousing has been around as a concept for decades, plug-and-play services like Snowflake are relatively new. Then there’s raw computing power. We take the ability to crunch big datasets as a given, but it hasn’t always been that way. In the past, complex computations and large databases could tie up machines for a long time.
That was before.
Technology’s improved a lot since then.
Databases live online and they’re accessible through open APIs. We have access to incredibly powerful machines via the cloud. Between Snowflake, Databricks, and Bigtable, you’ve got all the workspace you need.
Given the tools to report in real-time, businesses are doing some really cool stuff.
From good to great
Imagine you’re managing an old-school contact center. You’d probably have some primitive reporting showing how many calls are live at any moment, but that’s about it. Now, jump forward 20 years to a contact center equipped with real-time reporting.
Today, you can see not only the number of live calls, but call volume forecasts for the next hour, day, and week. By transcribing and analyzing live calls, you can understand common topics and themes. You can see the entire history of each customer: their customer journey, pain points, and experience with your organization. You access all of that data instantaneously with no delay for data collection, analysis, or reporting.
Those insights are gold dust for managers and leaders. They can help you make better decisions and scale faster. Say you know what areas of your business are under the most strain or which areas will be under pressure. Now you can make better hiring, investment, or development decisions—and make them before things go off the rails.
Immediate insights also unearth issues faster. If your contact center dashboard lights up with a geographic spike, that’s a good sign something’s gone wrong locally. If you’re a cable company, maybe you have a geographic outage. If you’re in logistics, it’s likely your vehicles have hit trouble. If you see problems like these early, you can get in front of them, solving them before your customers get frustrated.
Always monitoring, always improving
Real-time data exists in a bunch of different industries. My favorite implementation is healthcare, though. I remember a time when you had to go to the hospital to get your blood pressure or pulse measured. Now, my smartwatch tracks my vitals all through the day. As a runner, that’s really important for me.
It’s identifying when I’m stressed and highlighting when I’m in peak performance. Are my blood oxygen levels elevated? Is my blood pressure up? Is my body overly fatigued or am I ready to tackle this race?
No one imagined this sort of application when the first generation of smartwatches hit the market. Real-time data is an open-ended breakthrough. It doesn’t solve a particular pain point or challenge. We only discover practical uses once we have the data and can play around with it.
The business world is following the same trajectory. We’re in the early stages of discovery, collecting data and seeing what we can do with it. As more organizations roll out real-time data capabilities, new opportunities will emerge. They’ll discover new ways to scale faster, fresh ideas to improve operations, and novel ways to reduce friction. Personally, I’m really excited to see what they come up with.
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