How Qlik Helps Us Better Capture Your Science Fiction Imagination

It’s an unfortunate reality familiar to any manager: You have an important decision to make and not enough information to make it. The best you can do is conduct your own research and ask others who have been faced with similar decisions. Ultimately, your only choice is to decide like a true Jedi warrior. You must search your feelings and hope the Force guides you to the right answer.

In the real world, however, it’s not that easy. Far too often, business leaders are forced to make critical decisions based on guesswork. While experience and education can often give you an edge in decision-making, most of us would prefer a more concrete source of information. 

Unlike the myth of the Jedi’s Force, data presents a true source of unlimited power. Today, the modern Padawan must efficiently harness all aspects of data and analytics to guide their activities. No matter your industry, data analysis can provide some serious problem-solving tools. As we collect more data on a variety of activities and behaviours, we learn more about potential correlations and trends. Modern managers have more predictive tools at their disposal than at any point in history. 

The Facts Behind Supplying Science Fiction    

As a former accountant, I have always been obsessed with the insightful potential of data. There is no other source of information that can shed so powerful a spotlight on the machinations behind the scenes. In my current position with science fiction giant ForbiddenPlanet.com, I have the opportunity to collect a lot of information. 

ForbiddenPlanet.com is the leading science fiction retailer in Europe. We’re best known for our comic book subscription services available through our website, but lovers of science fiction memorabilia come to us for everything from lightsabers to TARDIS replicas. We have 130,000 products on our website, 30,000 in our flagship London store, and more in other stores throughout the UK. We’re also a comic book collector's dream, providing a variety of comics, graphic novels, and books that are available for purchase. 

While our product volume and diversity are all wonderful signs of a vibrant market and effective business model, we had a problem. The comics business moves fast. New editions are released on a weekly basis, and that gives us very little time to estimate the number of each product we need for our customers. The last thing we want is unfulfilled customer demand or old merchandise sitting on our shelves.

As a 26-year employee of the company, I watched the organisation embrace data years before it was popular. We started housing our extensive data history in our own bespoke systems as well as third-party systems, but we were missing a true system for the analysis of all this data. It was incredibly frustrating to understand the critical insights that were possible within the business but not have the tools to access those insights. 

Our management account meetings are a good example of the frustrations we experienced. Prior to every meeting, we were given an 80-page management pack containing a quarterly analysis of account data. Because the pack took more than a week to produce, we came to each meeting with data that was already out of date.  

Even then, it was nearly impossible to analyse dozens of pages of paper on the spot during these meetings. Almost every question asked was followed by a few minutes where attendees searched for the answers in their pack. Even as a person partial to data analysis, these meetings were not fun. The worst part was that every single meeting ended with more questions than answers. Any inquiries that could lead to significant insights were answered with, “I’ll have to check and get back to you.”

Voices Cried Out in Frustration...      

The comics business simply moves too fast for that kind of slow, clumsy study. After years of meetings spent flipping through pages and writing out IOUs for meaningful analysis, we knew we needed a new hope. After searching for solutions, we found two that could potentially serve our needs: Tableau and Qlik.      

At first, Tableau had the upper hand. Their engine already worked with our Claris FileMaker platform, and that presented an easy conduit for transferring data. Despite this advantage, I had my reservations. I’d tested Tableau with an export of our data locally from their desktop client and even though the tool worked as advertised, the process was slow. Since we already had nearly 160 million records at that point, speed and performance were key.

The turning point came during an impromptu coffee meeting with a Qlik consultant. I grilled Andy Patrick from Ometis for hours, asking for every possible application of the platform. Not once did I hear the word ‘no.’ I was sold on Qlik 10 minutes into our meeting; I spent the remaining two hours and 50 minutes (unsuccessfully) attempting to reach the limit of its capabilities. Andy was able to quickly demonstrate answers to my questions and I saw that Qlik was not only feature-rich, but it moved amazingly fast.       

...And Were Suddenly Silenced with Awe 

After I received a free Qlik Sense Desktop license, I took a week to learn the software. I was quickly able to take a deep dive into some product management analysis, such as determining our fastest and slowest sellers, where there’s excess stock, where we had no remaining stock—questions that weren’t even being addressed in our meetings. Once I had that, I decided to be a bit bold in my approach. I went into our next management account meeting with nothing but my laptop, and presented live analytics onto the screen.

Everyone was completely blown away by the speed and functionality of the platform. For the first time, we were able to analyse trends and answer questions about specific product performance during the meeting. Data went from an empty promise to a real-time decision-making tool. The mood changed from exasperation to awe and everyone was on board with the tool in minutes, just as I had been. The power of data was so compelling that within a week, the group operations director approved the purchase of 30 new licenses for Qlik Sense. 

By the time we began the organisation-wide rollout, the office was buzzing with potential. Two weeks after buying the licences, eight members of the team were already using it, including the head of retail finance, the head buyer, and the comics division. Most every other decision-maker at the company was also interested in Qlik, asking me, “Can you do me one of those Qlik things?” Everybody wanted an opportunity to discover potential insights for their unit.

Of course, with such a powerful and easy-to-use tool at our disposal, it became more important than ever that people understand data. With such an intuitive platform, the adoption challenge became all about data literacy and data governance. We had to know that everyone with access to the data was producing reliable reports. We also knew that data literacy would be an ongoing journey and education would be key. We made sure that every new user of the program went through a full training session. 

That was where I came up with the three Ts: tried, tested, and true. Users will not adopt a program unless they know the data is good and they can trust it. Before I went to that first meeting, I’d tested the data so I knew it was rock solid. Because of that, I was comfortable encouraging new users to test it for themselves. We taught users to try the program by creating reports using the current method, and then compare the data using Qlik. Once they knew the data reports produced from Qlik to be accurate, they all felt better about the integrity of the process.  

You Must Learn the Ways of Data      

You may be searching for the best platform to improve your organisation’s data analysis capabilities, or considering whether modern tools offer a significant improvement over older methods. You might even be at the stage where you’ve already selected a tool and are searching for the best adoption methods.

We’re a few years into our data transformation, and I’ve emerged from the process with a few pointers. First, make sure you start with good data, and understand the kind of data you need to make better decisions. There also has to be an internal commitment to processes that consistently provide top quality data.

This internal commitment is why my second point is the importance of starting at the top. Transforming your organisation into a data powerhouse takes cooperation from multiple teams. You may have completely different groups collecting and analysing the data, and a third management group may be responsible for utilising the insights. If leaders are not data-driven, it may be difficult to get consistent, useful cooperation from all groups.

Third, if you want the data literacy idea adopted widely through your organisation, you have to prioritise the experience of your users. With a tool as powerful as Qlik, it can sometimes be tempting to create overly complicated tools, but high adoption requires a careful analysis of the UX and UI designs in order to create truly functional and useful screens. Creating feedback and assistance mechanisms also help to ensure colleague involvement and engagement.

Only Data Analysis Is So Precise      

People frequently talk about the process of getting to success, but there isn’t a lot of discussion around what to expect when you achieve it. 

The first success that we experienced after embracing Qlik was the blazing speed of the adoption onboarding process. I am a two-time Qlik Luminary, spreading innovations and best practices of Qlik solutions. I presented to FileMaker users about Qlik integrations at a conference and at breakfast the next morning, a woman asked me for a few clarifications about the process. She mentioned that she had to complete a report that generally took about two weeks to create. When I saw her at lunchtime, she told me she completed that report in the time it took to dry her hair after breakfast.   

The second thing to expect is the profound impact that proper data analysis may have on your organisation. Instead of sifting through huge stacks of paper in cumbersome meetings, we now display everything on a screen. Our management team can now cover highlights within 15 minutes and that leaves us more time to look forward, not backward. We leave meetings with action plans rather than unanswered questions.

Every day, we find more data and analysis opportunities. Qlik is constantly evolving and there are features that we haven’t even unlocked yet. The fact that we haven’t been able to push the platform to its limits gives us great confidence in its scalability. We know the program will continue to provide us with valuable assistance for years.   

What’s more, a true data culture is growing within our company. We are more focused on what we know is important, and we move fast enough to take advantage of opportunities. Our retail division lives and breathes the platform and they’ve started taking the analysis outside the company to their supplier meetings in order to broker better deals. We already knew that online pre-sale behaviour could be a great guide to in-store consumer actions, but now we can use that knowledge to make smarter buying decisions.

In adopting a more data-driven business culture, we are finally able to navigate our fast-moving industry with the potential we always knew existed. Guiding your future by data is a profoundly different experience than hoping for guidance from the Force. It turns out that the world does work better if you’re on the good side—and the good side is the one with good data.