Exclusive insights: Thriving in the age of data-natives
DATA is the lifeblood of organizations today, and there’s data everywhere.
Whether finance or marketing, whether HR or operations, inside the business or along the value chain, there’s an opportunity to collect and analyze data and present it in a meaningful way to decision makers
Those who take this opportunity are able to deliver real-time insights that transform their business. Those who fail, will find it tough to compete.
In an exclusive interview with Tech Wire Asia, JY Pook, Senior Vice President, Asia Pacific, Tableau explains what businesses really need to focus on in order to really succeed with data.
Why is it so important for businesses to visualize their data?
Human brains are wired in a way which makes us respond to and process visual information better. Being able to see data in a visualized manner makes it easier for us to work with it and, therefore, tap into its full potential.
Additionally, visualizing data helps people tell a story better, minimizing the time taken to explain, discuss, and derive insights. Instead of showing rows of numbers, visualization presents data in the form of easy to read charts, graphs, maps, etc.
The visualization also allows users to emphasize important information by using color, placement, size or shapes to catch the eye. This makes it a digestible, visual format for all audiences to comprehend.
Making data easier to understand means people at all levels of an organization can work with it – not just IT or data analyst teams.
If businesses can apply this self-service approach to data analytics, people from across the business can ask questions of their data and make discoveries themselves.
This means business users can see their data presented in a way which allows them to gain insights into their queries quickly.
They can also present their findings to others more effectively, leading to faster, data-driven decision making.
Do employees from different divisions across the business need the skills to be able to visualize data? Why?
Our vision is that the next era in data is analytical ubiquity. Data is growing larger and faster than ever before, with IDC predicting that the world will generate 163 zettabytes (i.e., 1 trillion gigabytes) of data a year by 2025.
At the same time, organizations are looking to be more data-driven and everyone – from doctors to teachers to HR managers – has a reason to work with data.
By scaling data across the business, organizations empower more of their people to make decisions that can lead to all kinds of benefits, from saving money to gaining a competitive edge, to making the next big scientific breakthrough.
The traditional approach to data analytics relies on insights being provided by the IT or business intelligence (BI) teams.
For example, if Sales needs some market insights based on data, they would have to specify their requirements to the IT or BI department then wait for the results, hoping that what comes back is what they are looking for and within a timeframe where the data is still relevant.
The problem with this approach is that there can be a significant lag between the questions being asked and the answers being provided, meaning insights could be based on data which is now out of date.
This is why modern, visual analytics is important because it allows self-service integration of data which leads to quicker, better-informed decision making.
Self-service data visualization also reduces the reliance on IT departments, which face tremendous pressure to deliver business and strategic value.
Furthermore, many organizations are also struggling with a talent crunch due to a shortage of workers with data science and analytics skills.
It’s also important to remember that while anyone across an organization can use data in some way, their requirements will be very different.
Some people need to do very sophisticated data modeling, while many simply want to view and interact with data in a way they can understand to help their decision making.
Companies need to be able to adopt an analytics platform which caters to different levels of requirement – at a reflective cost – rather than a one-size-fits-all platform. This will make it easier for them to put data in the hands of even more people across the business.
Grab is a good example of how a company is effectively using visual analytics across its business.
Grab adopted Tableau to centralize millions of rows of customer data and help the business make data-driven decisions around app development and overall user experience.
What does it take for companies to scale their data across the organization?
People in all types of organization, at all levels, can use data in some way. However, there are two significant problems stopping organizations from putting data in the hands of everyone.
The first is that not everyone uses data the same way. Some people do advanced analysis and create complex data models. Others may just have simple business questions they want to explore and understand.
The thing holding many organizations back is that they don’t have any easy way to deliver the right level of analytics access to all of them.
This is why we’ve introduced three new tailored subscription offerings – Tableau Creator, Tableau Explorer, and Tableau Viewer – which enable organizations to empower their entire workforce with the right level of capabilities for each unique need.
The second issue for organizations is that organizations cannot readily analyze much of their data because it is in the wrong shape or coming from disparate sources, so getting it in a useful form can be a complicated and time-consuming process.
If people have to wait for a specialist to clean, shape and prepare it for analysis, it might then be out of date by the time it’s available to use.
As more data gets created, this becomes a growing problem. In fact, data prep is one of the biggest challenges facing our customers today and a recent Harvard Business Review study says data analysts spend 80 percent of their time prepping data while only 20 percent analyzing it.
That ratio must be inverted. We think people should be able to spend more time on the most valuable important thing – the analysis.
We also think it makes more sense for people to be able to prepare and then analyze their data within one platform.
Does the statement, “don’t just be a digital native, be a data native” resonate with you? Why do you think it’s important to be a data native?
As the volume of data has exploded in recent years and we continue to generate vast amounts of data from here on, people are recognizing the value that lies in analyzing and drawing insights from data; we are entering the era of analytics ubiquity.
Just as digital natives have emerged in an era where the use of PCs and the internet was ubiquitous, similarly data natives will emerge as data and analytics becomes ubiquitous and using data becomes second nature.
It’s primarily the vast benefits that people recognize can be derived from data that makes it important for us to move in this direction.
To make this a reality, collaboration is necessary within the ecosystem including the government, private sector, and educators.
This is a process that won’t happen overnight, but we are seeing steps taken towards this goal. Academic institutions for one, are beginning to incorporate analytics into their curriculum, even in non-IT courses.
Take for example Singapore Management University (SMU), which has introduced a Human Resources Analytics course as part of its Organisational Behaviour and Human Resources major.
The course teaches analytics skills in an HR context, recognizing that today’s students need to go into the workplace with an understanding of analytical tools, as well as hands-on practice.
While data is exploding, access to and comfort with using data is important on the journey towards becoming data natives.
To this end, we’re seeing the government providing open access to data. Through the Open Data Portal, Data.gov.sg, citizens can play with datasets covering several areas which affect our everyday life, from the economy to transport.
This helps people increase their familiarity with data, and has even led to some creating services and apps that solve real-world problems and help their fellow citizens.
The Government is also taking active steps to upskill the workforce. For instance, at this year’s Budget, the Government announced the expansion of the TechSkills Accelerator (TeSA) programme, which is aimed at helping people upgrade and acquire new skills and domain knowledge.
As part of this, an additional 20,000 training places will be created by 2020 with courses targeted in frontier technologies.
With so many initiatives from government, educators, as well as industry, the importance being placed on analytics is clear.
Visual analytics tools, combined with increasing education, mean it is now possible to put data in the hands of everyone.
We are in an age of data ubiquity, so we must embrace these initiatives to become data natives and truly harness the value of data because the potential is limitless.