Data is indeed the new oil for successful modern businesses and organizations. But what exactly is data? In simple terms, Data is a collection of different types of information that is formatted in a particular way and can be examined, analyzed, and used in making meaningful decisions.
In a business context, it’s all the information collected by organizations, such as information about the customers; who they are, what they buy, what services they utilize, what marketing materials they engage with, etc. Data is generated in almost all the activities we conduct.
The power of data has been stated globally by successful leaders, businesses, and governments. This is evident in the digital economy where more customer and organization data is processed and analyzed, hence providing business visibility via trends and other insights that help make better decisions, that drive efficiency, competitiveness, and profitability.
However, it’s not just about having data that creates a competitive advantage, it’s the kind of data collected, how it’s collected, its quality, and what organizations do with their data that counts.
Before organizations had computers, which people thought would render them jobless, they used old-school methods of data storage such as files and folders. From medical records to loans, banking and insurance, they would write up your file, put it in your folder, and get a clerk to put the folder in the right file cabinet, which is not only a chaotic task but also tiresome.
It was even crazier that the government would pay its employees in cash and banks were supposed to store all those files. In this system, your files would simply sit idle and would only be viewed in isolation for assessment and decision-making. Analyzing all files for trends and statistics would take a significant amount of time and labour, take months and cost a lot of labor and costs, denying business an edge to quickly scale.
It is great that we don’t live in that world anymore but surprisingly we still exhibit similar habits. How do you ask sectors like the Kenya Police, to mention but a few, still manually key in data in occurrence books!
According to statistics, an average of 2.5 quintillion bytes of data is created every day and more interesting is the fact that 90% of the world’s data has only been created in the past 2 years. This means technologies are advancing and methodologies are also changing and they have resulted in businesses scaling as a result of data.
With this development, we can’t rely on spreadsheets to analyze data. We need to have the right data talent to be able to keep up with skyrocketing growth and to make the right decisions based on data. Here’s a case in point:
Safaricom, a telecom giant boasts so many customers and a variety of services offered 24/7. The amount of data they collect on a daily basis is mind-blowing! Would spreadsheets be efficient in such a scenario? Absolutely not, but big data would. Analysis for one spreadsheet is easy, but if you have many of them, it will take a lot of back and forth, copy and paste, deletion, duplication and modification. All kinds of madness!
Anyone who has gone through this process will agree that it is inefficient and time-consuming. With the world generating huge amounts of data, it is critical to adapt. Technological advancement is key in handling data and scaling businesses. With such volumes of data, big data technologies have emerged in the field and giant organizations such as Google, Microsoft and Amazon have dominated this space.
Big Data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.” – Chris Lynch, Vertica Systems
The problem is never the data. The elephant in the room is knowing how to use the data. Many organizations have huge data silos with less or no knowledge on how to effectively utilize the data and no one cares! Such cases are a result of organization culture, operations team and lack of skills, while in others its executives are just scared of technology and prefer the old system, probably due to a fixed old mindset leading to very little value out of the data.
Start-up, telecommunication, health industries and financial institutions are at the forefront of adopting necessary technologies to offer data solutions. This means the demand for data scientists is high! In fact, data science jobs are considered the sexiest in the 21st century as they continue to boast of huge pay. We are talking about Ksh 150,000/month for a junior data scientist!
So, knowing all this, do you have the necessary skills to take up such opportunities? Does your organization offer employee career growth? JENGA School has taken the initiative and partnered with organizations like M-kopa to upskill their employees and the outcome has been amazing!
JENGA School offers Programs in data science to equip you with the right data skills. You can either enroll or work with your employer to sponsor you to upskill.
How can organizations, especially start-ups realize that their data is helping them to scale? This is not a yes or no question, but a process referred to as data maturity. Its goal is to help businesses utilize new and existing data to extract meaningful insights, with minimal effort so that they can focus on making better decisions and getting work done effectively.
It has been a great honor and privilege to lead my team which includes Mark Karake, Founder & CEO of Impact Africa Network, Mathenge and Dr. Albert Kahira at Impact Africa Network’s Data Lab to come up with its very own data maturity framework, which can be reproduced to help its brands, including JENGA School, to be data mature organizations. We learn every day, right?
Data maturity is critical for organizations and businesses to scale. The more data matures, the clearer it is to identify new opportunities and threats. For instance, through leveraging the power of predictive and prescriptive analysis, a data-driven organization is able to predict the future and take the necessary steps. It can accurately predict the number of sales of each product in a given month and implement strategies like using promotions to increase sales.
Data-guided organizations can foresee potential threats or challenges; such as which months of the year are faced with decreased sales and can take preventative measures in their favor. A study by Splunk found that organizations making use of data had increased revenue and reduction in operational costs, boosting profitability by an average of 12.5% of their total gross profit.
In my next article, I will highlight the stages of data maturity, the process of setting up the data maturity framework, how to measure the success of the implementation as well as the best tools and techniques to use.
The moral of this article story is simple – data maturity equals better control over your organization’s financial health.
In the meantime, intake for JENGA School’s Data Science programs is ongoing, apply today!