When it comes to building a data-driven culture in the business, over 70% of companies are the first to admit that they have no such thing as a data culture in place, according to the 2019 Big Data and AI Executive Survey by NewVantage Partners. The survey participants represent large corporations, such as Ford Motor, Johnson & Johnson, or even American Express. This asks an essential question for all businesses: If big corporates can’t manage to bring data at the heart of their business strategies, how can small companies expect to succeed?
Critical obstacles remain to overcome for companies to start seeing the benefits of a data-driven strategy. However, big data investments have been part of large business processes, with AI and big data financing exceeding $50MM in 2019 for over 50% of participants. Large companies are also developing methods and organizations to make the most of their data. Almost 70% of corporates have staffed data expert roles, such as Chief Data Officers, since 2012. But the fact remains that despite making data more accessible to the company and creating a dedicated structure to support data culture, commercial giants are failing to make it work. There can be only one conclusion: Money, while significant, is not the sole factor of data success.
Consequently, if we want to pursue the build of a world of data intelligence where the information that devices and tracking tools collect can be repurposed effectively for decision-making and growth, we need to put the finger on our data obstacles. Data is everywhere, and we’ve made sure we can establish direct access to the majority of business-essential data. How come we are not making the most of it? Identifying the obstacles that all companies face on their path to a data-driven structure can help create a data-friendly process that is beneficial to all.
We get “carried away”
The purpose of data is to provide informative background about events, individuals, and markets. In an ideal world, data should offer the insight a business needs to shape its offering and meet the market demands. However, more often than not, companies that are launching new products or services can get carried away in the innovative and creative process. To ensure that a new idea is viable, the first step is to confirm it against market and audience data. Are people likely to buy your new product? Does it exist already but in another form made by a competitor? Does the idea bring something new? Data can answer all these questions and many others effectively. However, innovation excitement can cause many businesses to remain blind to the information provided by their available data. You have an idea, and you feel it is too great to bother checking or comparing against real market data.
We can’t visualize it effectively
Most businesses are familiar with displaying a limited number of data within a fixed visual display. Pie charts and graphs are an essential tool for every business board meeting. But when it comes to visualizing large volumes of different data in a meaningful and versatile format that can showcase real-time fluctuations, many businesses hit a wall of bricks. Using data effectively begins with the ability to create a data grid and data streaming feature that lets you see and understand your data. As such, it becomes necessary to direct investment towards meaningful visualization resources, such as using user interface React components library by Infragistics. Having the right components to build data-rich apps that can provide financial and business charts in real-time is a game-changer for decision-makers. Failure to create a compelling and accessible data visualization tool can affect data understanding, data reading, data use, and, inevitably, informed decisions. Many companies knowingly choose to ignore significant data because they can’t integrate them meaningfully into the decision-making process.
We simply don’t understand it
Is visualization always a problem? The answer is no. Data, while being accessible to all companies, remains a confusing business element. According to Neil Patel, Google Analytics is the preferred web traffic data collection tool, with over 40 million sites using it regularly. It is free to use – but there is a premium version available too. However, despite its availability, Google Analytics remains a mystery for many users. While setting up a Google Analytics account and checking visitor metrics are some of the most common activities, very few businesses take the time to make the most of the tool. It has become a habit to collect figures without any further analysis. Fluctuations are observed and monitored closely, but lack of knowledge of the many functions means that businesses are missing strategic data processes. Some of the most common issues that users face, for instance, relate to setting up meaningful goals, identifying flow issues, boosting site speed, and managing engagement rates.
Now, Google Analytics is a tool that most businesses implemented over 10 years ago. While still misunderstood in places, it is a tool that people are used to seeing. How does this translate to more recent tools that have a smaller market penetration rate?
We’ve got too much of it
Most businesses are data-rich, but they are poor in data-based knowledge. John Dillon, CEO at Aerospike Inc., explains a common obstacle that affects data management. Data is coming at high speed and volumes into the business. With a large variety of tools to collect data, and other data-recording services, companies can rapidly build a pool of information. However, the innovations that have driven the recording and reporting process are still to be matched with an adequate interpretation and analysis structure. When the volume becomes too much to handle and make sense of, the collected data becomes meaningless. Additionally, fast-paced business processes make it challenging for data analysts to perceive meaningful and actionable information patterns. The task is too overwhelming, and unfortunately, analytical innovation still has a long way to go to farm data effectively and in real-time.
We don’t ask the right questions
It becomes evident that collecting data serves no purpose if it can’t be analyzed and utilized adequately. The concept of reducing the volume to enable effective data analysis can provide relief to your team. However, it is only useful if the business understands how to make the most of the information. If you ask the wrong questions, you can’t use data to support future decisions. Companies entrust their team to make sense of the collected data, but often fail to define which KPIs are relevant for the business strategy and growth. Many also fail to validate the quality of their data, which means they potentially keep incorrect data for further analysis. Reviewing sources, collection types, and life expectancy of collected information can help organize knowledge accordingly.
We believe it reduces our creativity
Data is a source of knowledge, which is essential to design effective strategies for business growth. In many ways, data plays a similar role as a compass on a ship: It provides a direction. In creative businesses, however, teams feel limited by the use of data. Many fear that using data reports and analysis extensively can affect the creative spirit of the company.
Where does the belief that information impacts creativity come from? More often than not, failure to extract meaning from the collected data can deter creative teams from using it. As a result, the creative process is bent and shaped a posteriori to bring the data in perceptive. The process is damaging and frustrating. To support creativity in the business, data needs to become part of the initial brief and the proof of concept in later stages.
We are data-blasé
The advantage of data is that it’s everywhere. But it is also its biggest problem. Indeed, nowadays, users can share a variety of information about their preferences and lifestyles. The Internet of Things also adds another dimension to profiling, ensuring that people who use IoT devices, such as fitness trackers, for instance, can provide helpful, in-depth insights. But with hundreds of different pieces of information available for each customer, the question needs to be asked: How much do we really care to remember or use? Fitness trackers, for example, can track health data, such as sleep, heart rate, and physical activity. But some also provide extensive insights into an individual’s purchases – with NFC contactless payments –, location, and even menstruation. In a world where we get to know every detail about everyone’s life, it can be hard not to be tired of this omniscient knowledge.
Is your data trustworthy?
Users are savvy. It is the 21st century, and many customers are not willing to share more than strictly necessary. Can an online business truly trust a user’s date of birth, name, contact details? How many visitors enter a fake email address to get rid of a newsletter subscription popup? How many underaged users tweak their year of birth to access sites that wouldn’t be suitable otherwise? Businesses have a lot of work to convince their audience of the benefits of sharing reliable data.
Before we can build a data-driven culture that supports effective decisions and growth, businesses have to address the many shortcomings of our relationship to data. As we use it nowadays, data is not always trustworthy, meaningful, manageable, and accessible. Changing our attitude to the tools and knowledge we use and collect needs to become a priority if we are to build the future of data intelligence for all.