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Qlik Connect 2024 - in a sea of data, how to make sure customers are waving, not drowning

Alyx MacQueen Profile picture for user alex_lee June 3, 2024
As Qlik's annual conference begins, General Manager Brendan Grady shares what has changed in Business Intelligence in recent years, and how customers are adapting to new technology and releasing their grip on spreadsheets.


The world runs on data. No sooner do organizations plug in a new tool or system than the data begins to flow. Analytics tools have come a long way, but, let's admit it - users are still grimly clinging onto Excel spreadsheets. Are buyers still wrangling with the same data issues as they have for years and years - or are they facing new ones? In fact, how has the wider data landscape changed? And why is making the change from siloed data often easier said than done?

Brendan Grady has been in the analytics and data space for his entire career, going all the way back to post-college sales, via Cognos and IBM, to his current position as General Manager of the Analytics Business Unit at Qlik. His view today is that he's seeing an ongoing issue of paralysis by analysis:

The amount of data that's being thrown at people is not slowing down, in the amount of data sources that everybody has to bring in to make decisions and more importantly, to make confident decisions they need to bring in more data sources.

I think the biggest challenge that you've seen is that people don't even know where to start half the time. One of the more complex things that I always challenge people on is can you access all the data sources? Often the answer is yes. But then there's a deeper challenge that many customers are seeing - it's the amount of data and the ability to model it so that humans can do something with it, someone that may not have a technical skill set.

The importance of acquired knowledge

The topic of up-skilling to use new tools isn't a new one. The term "data-driven decisions" is being happily bandied about by vendors selling out-of-the-box solutions. Technology has done a lot of catching up - and Grady agrees that generative AI is changing the way that companies look at data:  

What's happening in the market around generative AI is forcing everybody to think about this differently and how we go after the problem. We're in an era of required knowledge. It's just expected that we have the answers at our fingertips all the time. And for those people that don't have access to that acquired knowledge or worse, ignore it, there's a cost associated with it. That could be loss of employment. It can be sensational news headlines for companies that have gotten AI and data wrong. That pressure is coming in on every organization on top of this. So you combine that with the increasing number of data sources and people get a little bit of the ‘deer in headlights’ scenario.

Grady acknowledges that learning new ways of working can also be draining, saying:

It's why so many people turn to Excel as their 'analytics' tool. But a quote I have from a Forbes article said that 85% of spreadsheets have a mistake in it. So now imagine you're a large multinational corporation making multibillion or multimillion dollar decisions based on pivot tables and pretty pictures in Excel. People turn to it because it's familiar. It's fast and it feels good.

That said, it's certainly a lot harder to distract an audience with a few colorful pie charts. Grady also believes that the attitudes of the workforce are changing - and that's before you take into account the younger generations who don't have a spreadsheet habit to fall back on when data feels scary:

I think as you look at the digital natives - people that grew up with these, they are going to force vendors to think about how these products work. Analytics isn't going to be a place for you to go, AI isn't going to be a place for you to go. It's going to be embedded in everything you do.

Customer experiences

Qlik's approach to data modeling and visualization is designed to uncover patterns that traditional methods might miss by surfacing critical insights through automated modeling. Comfort blankets aside, it would be naive to assume that an organization juggling massive amounts of siloed data can magically transform it with a new analytics tool. There's still an amount of time that needs to be invested in data cleaning, says Grady: 

If you don't get that foundational data right, it's like doing a math problem where you start with the wrong numbers: you're gonna end up in the wrong spot. So what we're seeing from our customers is that they realize the business intelligence stakes with are high. Even if you bring in Machine Learning, predictive analytics, more AI capabilities, if you don't go all the way back and understand that that data quality was critical, it's going to get even worse and there are consequences when you get it wrong. So our customers are pushing us for it. And the way we are responding is by approaching it holistically - with data BI and analytics BI as two sides of the same coin. 

Grady shares two examples of how Qlik's impact extends beyond the confines of corporate efficiency, touching lives and communities. 

Kendra Scott Jewelry faced skyrocketing data costs, with monthly expenses ballooning from $19,000 to $180,000. They also needed to optimize their merchandising strategies. Grady challenged the firm to stop looking at trying to just focus on what was performing well, and look at the grey areas of products that shouldn't be marketed together. Qlik's solution allowed it to identify ineffective marketing combinations, leading to a significant shift in strategy. During Black Friday amid the pandemic, these insights generated an additional $5 million in revenue. Moreover, the company managed to reduce its data costs to $27,000 a month - and donated a large portion of those savings to charity.

Continuing the theme of the broader social impact of these business optimizations, Direct Relief is a humanitarian organization that uses Qlik to analyze patterns in conflict and disaster zones, enabling them to deliver medical supplies more effectively. Grady shares a poignant example of how Qlik helped predict cholera outbreaks in Madagascar following unprecedented typhoons.

They saved hundreds of thousands of lives because they were able to find patterns within the data. The same analytical prowess is applied to tracking refugee movements in Ukraine, ensuring aid reaches those who need it most. They thought that people would go just to the border and stop. But because they could combine more data sources using Qlik, they found that many refugees went deeper into Poland and actually a lot went to Hungary - and they wouldn't have been able to find that with a traditional visualization tool.

My take 

On the eve of the Qlik Connect conference in Florida this week, it was refreshing to have a conversation that didn't automatically zone in on generative AI. We did touch on the subject, but Grady's emphasis was on making it part of the workflow rather than a standalone solution. Grady joked that he's often quoted as saying, “Friends don't let friends use visualizations to make life altering decisions.” His enthusiasm for data analytics and the benefits for customers and users was palpable.

I'll be on the ground in Orlando over the next few days to find out how customers are handling the transition from legacy tools with Qlik's holistic approach while under pressure to show a return on investment.

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