This is the second part of the Data Literacy for Professionals article
Examples of Data Literacy in Practice
Data literacy adds value to an organization in various ways, one of which is to support decision-making. Say you need to create a new marketing campaign to increase customer retention, for example. Where would you start? Would you just come up with a few random ideas, select the most promising ones, and run with it? A data literate professional would take a step back, examine the data at hand, see if there was a way to collect additional data, if necessary, and then work with some analyst to make sense of it all. Then, upon contemplating the insights gathered from this analysis, he would find some practical alternatives and discuss them with the marketing team (which might be even his immediate subordinates). Afterward, he might want to dig deeper into a specific option or two and after examining the corresponding data and insights further, come up with a data-backed decision to present to the marketing executives.
Another example of how data literacy would add value to decision-making could be UI enhancement, a vital part of the UX. For example, say that the site doesn't get many people to click on the "buy" button. Someone identifies this problem by observing how the sales funnel is and brings it to your attention. You then explore various alternatives for making the "buy" button easier to stand out, perhaps experimenting with its color, size, etc. Which option would you go with, however? If you are data literate, you get the help of a data scientist to design an experiment, run it, and come up with some insights as to which option yields a better click-through rate. This analysis can involve some statistical tests too. You'd then think about all this, evaluate its reliability, and decide on the most promising option for the button based on the results of this analysis. This mini-project can help improve the UI and possibly the whole UX, driving more sales for the company.
New products and services can also come about through data literacy. For instance, you could have a new analytics service for the users made available either on the website (if each user has an account there) or via an API. Perhaps even something geared towards a more personalized interface, based on the user's behavior on the website, an interface that can even change dynamically. All these may seem like magic to someone unaware of the potential of data but for a data-literate professional, especially someone with a bit of imagination, they are as commonplace as a coffee shop.
In the competitive world we live in, getting an edge is paramount and something that data literacy can enable. Data literacy can help solve problems faster and more reliably, come up with new viable products/services based on data, and even bring about a more efficient and transparent culture in the organization, one based on a data-driven mindset. Additionally, data literacy can help make the most of the specialists involved in data work, improve employee retention (for these and other information workers), and transform the organization into a place that keeps up with the latest tech developments. An organization like this can foster more contentment and efficiency in its employees and enable them to commit long-term. A place like this can help individual professionals in many ways while at the same time benefiting other people involved, such as users and customers. In times like these, when the economy and the market are unstable, such improvements can bring about stability and even growth on both an individual and a collective level.
Data literacy isn't a nice-to-have, not anymore anyway, but a necessity for any organization that wants to keep its place in today's increasingly digital world. A company comprising data-literate people, especially managers and other knowledge workers, can leverage resources it didn't know it had because they are in the form of data. Also, it can make it more agile as it can explore acquiring additional data resources and using them to improve existing data-related processes and services further. This company's competitors are probably doing this already, so it's no longer a luxury to invest in data literacy and use it to cultivate a data culture and make data-driven decisions.
Data literacy also helps individual professionals through a series of specific improvements. For example, a mid-level manager can become more data literate and have a more modern approach to tackling the problems her team faces. Additionally, she can hire new members or train existing ones so that they can become more competent in handling and analyzing data to tackle the tasks in their workflows. Maybe even discover new ways to deal with bottlenecks and other issues that hinder efficiency. All that progress might eventually manifest as a promotion for that person and other people on her team. And if that person decides to leave that organization, she can have more options in future work placements and even new roles, thanks to her data literacy ability.
Overall, data literacy is a powerful tool, or mindset and skill-set to be more accurate, for leveraging data and making better decisions accordingly. It is very hands-on and benefits people and organizations in various ways. It involves understanding data and how we govern it, analyzing it effectively, presenting and communicating the insights discovered, and protecting data/information, among other things. It entails understanding where privacy fits and taking actions to keep data related to people's identities under wraps. Data literacy is closely linked to data strategy and having a data culture in the organization. Being literate about data can also give professionals a competitive advantage over their data-illiterate colleagues and make a company more agile and relevant in the market. Especially when it comes to complex problems and difficult decisions, it can help bring about more reliability and objectivity to the whole matter. This leveling up can enhance the organization overall, along with everyone associated with it, be it partners, vendors, and, most importantly, its customers and users.
To learn more about data literacy, feel free to explore the corresponding page of this site. Cheers!
Zacharias Voulgaris, PhD
Passionate data scientist with a foxy approach to technology, particularly related to A.I.