We’re a customer-obsessed organization, always looking to go the extra mile to understand and support our community. That’s why we like to hold regular roundtable discussions with business leads and tech innovators – to learn how data is being used out in the field, and get insights on the key challenges shaping their strategies.
And while we can’t share with you the names and businesses of those who attended, we can give you the low-down on what was discussed. So, here are the top three themes we uncovered at our latest discussion, which focused on data lakes. Enjoy.
1# Self-service is here to stay, but it comes with challenges
“I’ve got my data lake, now where are my insights?” asked one participant in mock exasperation, summarising how organizations who break down data silos often believe technology will be a magic solution for their data strategy. Obviously tech plays a part, but it’s crucial that data users have the skills as well as the tools to access and extract the insights hidden within their data lakes.
This kicked off a discussion about how best to manage the demand for self-service business intelligence – and the challenging task of truly democratising data.
An attendee from the tech industry said of their current strategy, “The business wants to keep on doing business, and still wants to use data. But they want to do that with self-service analytics with less dependency on technology, by making the team more data literate.”
Another participant reflected on the challenges faced by IT departments to meet this business demand. “To improve the customer experience in a particular market we need to understand where we need to start and how to price our product. For that, if you put a dependence on IT to prepare the data for the business, it takes a lot of time.”
And although democratizing data – removing the IT team from the equation – might seem like the obvious way to solve this challenge, there was a note of caution from one participant.
“With multiple stakeholders you can’t define the guardrails. I might own the data, but I can’t set the rules of how the business use the data. So, when democratization is introduced, you need to have the vision to define parameters of how it’s used – and the restrictions around the data.”
#2 Good data governance leads to better insights
All the participants agreed that regardless of technology, good governance is key in helping to sort the good, bad and the plain ugly from the increasingly large data volumes that make up our data lakes. This is how you stop your data lake becoming a stagnant data swamp.
“Analytics are what’s going to get you results, but you always need governance at the foundation,” said a data leader in healthcare. “For example, if you were really looking at success factors in your business the integrated data roadmap you create will need everyone to come to the floor and design the throughput for that.”
Another participant agreed. “Driving any data analytics where there’s no governance framework is not going to work. Insights are important but without the governance the accuracy gets compromised. Which means you can’t rely on it.”
One healthcare participant believes leadership is key, “We need to democratize data governance – not just the data. This is where you’re talking about a CDO laying the foundational infrastructure to empower the business to govern their own analytics projects. Business is a lot smarter at doing IT now, so with the right leadership, that’s the next phase.”
#3 Data on productivity during the pandemic needs context
No roundtable in 2021 would be complete without discussing its impact, so while it may have been off-topic we were pleased to hear from our attendees about their experiences of the pandemic. The feedback suggests that each industry experienced working remotely slightly differently.
“Like everywhere data use has increased with the lockdown across the healthcare sector, be it with online appointments and predictive outcomes. But I wouldn’t say this will be a permanent trend. With patients, you will always need that human connection.”
Others agreed that any trends that appear to be emerging on working behaviors should taken with a pinch of salt.
“Of course in surgery you still need a surgeon in the theatre. But for other data-centric organizations, say marketing or IT, it seems a lot can be done from home. The pandemic initially created so much panic about whether we were able to deliver what we needed. ‘Can we have 8,000 users downloading reports from remote work?’ Turns out the answer is, yes.”
But as other mentioned, any data on perceived efficiency drives need to be assessed in a less reductive manner. “The data might show productivity is up, but at what cost? Is it giving a good work life balance – and can it be sustained? For some families it’s good. For others it’s not. We really need broader set of data collection on that.”
What does this mean for your data strategy?
With so much to consider – both in terms of your technology stack and business culture – it’s important to have a clear set of goals for your strategy.
As one participant summarized, “Ask what’s the right solution for the right problem. There’s no one size fits all solution. ROI is the best place to start – look at what you want to achieve from the business standpoint and build back from there.”