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Achieving A Data-Driven Culture

We talk to Mico Yuk, founder of BI Brainz Academy

28Apr

Mico Yuk is the author of Data Visualization for Dummies and founder of BI Brainz and the BI Dashboard Formula (BIDF) methodology. She has trained thousands globally how to strategically use the power of data visualization to enhance the decision-making process, working with Fortune 500 companies including Procter & Gamble, Honda, Kimberly-Clark, Royal Dutch Shell, Nestle, Qatargas, Ericsson and FedEx. We sat down with her.

How did you start your career in data?

Weirdly enough, I actually started my career in SaaS as a data scientist. Data was my currency. Without data, you were dead in the water. My job was to create and run algorithms that delivered and proved the stats that were being published by Forbes about our high-profile college football team. A few years later, I entered the business intelligence world. What a big change! Everything in this world was Excel. No one had to prove their numbers. The realization that I had a lot of ‘data discipline’ to bring to the table and the BI industry is how my love affair with data started.

How have you seen the industry change over the last decade?

In the last 10 years, technology has changed and business users' expectations have changed. However, the challenges have not. The prevalence of big data coupled with disruptive tools such as Hadoop, IBM Watson Analytics, SAP HANA, Tableau, Qlikview and Domo are redefining the analytics industry. The traditional BI vendors are being forced to reinvent their old BI tools or become extinct. The emergence of IoT has created an insatiable thirst for advanced analytics, which in turn has driven a demand for data scientists that the market can’t meet. Wearable and smartphone devices continue to shrink the consumer viewing real estate, forcing the display of billions of rows of data into a single number or chart. It’s both exciting and scary. 

One thing that has not changed is the business vs IT challenge. The traditional data wars of ownership versus stewardship. Many BI teams are at risk for becoming ‘BI-nosaurs’ (per Gartner), as they struggle to deliver value to the business. Ten years ago, IT teams controlled the company’s technology spend. Today most CIOs can't secure a technology or resource budget without gaining extensive business review, buy-in and approval. This has meant that lots of technical people have basically become pseudo marketers. The second hottest addition to the C-level in most progressive companies, besides the Chief Digital Officer, is the Chief Analytics Officer (CAO). The creation of the CAO role signals a data revolution, where users are demanding knowledge and not just more information. I hope to see this trend continue.

What do you see as the major challenges confronting the data viz project over the next few years, and what technologies do you think will be game changing?

When used properly, a data visualization is the most powerful way to communicate data. Human being recall images 60,000 times more than they do text. However, most organizations face the same three challenges: 

1) Data. Having the right data is going to be one of the key challenges, and the time it takes to validate the data. It is important to measure the right KPIs or metrics, as looking at the wrong ones leads to data visualizations that contain lots of information but no real action or insight, and ultimately a lack of user adoption. 

2) Design. A lack of design and UX skills will also hold organizations back. Traditional data visualization thought leaders like Stephen Few, Rolf Hichert and others subscribe to the black and white, less is more approach. Today, users expect their business intelligence assets such as dashboard and reports to look, function and perform like the apps on their phones and desktops. Users want personalized, user friendly, aesthetically appealing, and easy to understand data viz that provide clear actions. 

3) Tools. Old BI tools vs new BI tools. One uses a ‘single version of the truth’ the other promotes data silos. The solution to these problems is not just better technology. In the last nine years of building the BI Dashboard Formula (BIDF) methodology, we realized quickly that the biggest problems reside with the people who were using the technology. That is why BIDF techniques are 50% right brain (soft skills), 50% left brain (analytical skills). We provide tools and strategies that facilitate clear communication.

How important do you think it is for an organization to build a data-driven culture? To what extent do you think data visualization enables them?

' In God we trust, everyone else brings data.' (William Edwards Deming -- a renowned American statistician, professor, author, lecturer, and consultant.)

Although that saying is from the 1950’s, it still holds true today. Data-driven cultures are a must for large and small organizations. The rise of big data and ‘other’ types of useful data marked the death of ‘gut analysis’ (the number feels good analysis).

For organizations to take advantage of the opportunities that IoT and big data present, companies must not only promote but also reward data-driven individuals. Insight cannot be gained by asking a single question, true insight is learning the question you don’t know to ask. Organizations need their data to become intelligent, and they can only do so by empowering the individuals that own it. Data-driven cultures that are evolving go from reporting data to telling visual data stories that inspire and invoke action. This is where the BI Dashboard Formula methodology can help.

How to do you go about creating a data culture? Is it better to start from the top down, or work bottom up?

' Without data, you're simply another person with an opinion.' - Jonah Harris

This is the message that the leaders for data-driven cultures have to embed in the DNA of their organizations. Creating a data culture must start from the top, with leaders who demonstrate the importance of data-driven decisions. Leaders should start by first presenting and demanding data for all decisions, then encourage all managers to do the same. Leaders must also set examples, by rewarding data-driven users whose actions provide a measurable impact to the bottom line. Data source and hygiene should become the number one priority.

A recent Business2community survey of data professionals found that the data science skill with the highest correlation to project success was data mining and visualization tools. Do you agree with this?

'Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway.' - Geoffrey Moore, Author of Crossing the Chasm & Inside the Tornado

To the average person, data scientists are geeks who take data and build monster algorithms to find little nuggets a company can use to understand the most complex problems. What is often forgotten is that once those nuggets are found, the main value of data scientists is their ability to tell a story with that data that the anyone can understand.

The data mining part is not surprising, but I know that for many in the analytics and business intelligence industry, they don’t realize that the only way for a data scientist to communicate their findings with the average Joe Some (non-PhD) is by using simple visuals and telling stories. Otherwise, their insight is useless to a company.

What makes a great data visualization?

'The greatest value of a picture is when it forces us to notice what we never expected to see.' - John Tukey, American Mathematician

Great data visualizations tell stories. Not just pretty stories, but stories that provide insight, outcomes, and actions. Telling a good story is not complex, but the simplicity is where most fail. A great story does not tell you everything, just the things you need to know. Great visualizations don’t need to be explained. There are many schools of thought that focus on the design elements of great data visualizations such as Edward Tufte, Stephen Few and Rolfe Hichert.

In my BI Dashboard Formula, we focus more on telling the story. A good story doesn’t need to be pretty, it just needs to simple and useful.

You can find out how to apply Mico's methods to your own organization with her online course, which is open for enrollment from the 23rd of May. Register here today.

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