Data Science and Your Business

British mathematician Clive Humby famously declared “data is the new oil.”

As a petroleum engineer that quote got me! When dug deeper into it I realized he meant that "data, like oil, isn't useful in its raw state". It needs to be refined, processed, and turned into something useful; its value lies in its potential. Be it the gas in your car, or the plastic components in the mobile device you are holding in your hand, or numerous other areas of your life you make use of the oil... Same approach needs to be practiced when talking about data.

Let us start with the process of extracting the data. The business must commission the site for extracting the data, it could be an automatic data collection (like a combination of IIOT and ERP systems) or a manual labor (could be spreadsheets). -- I will share more on how to collect data in later articles. – At this point, there might be a need to use third party contractors to assess the data quality and examine the usability of the data. Also, the business needs to keep in mind the process of transferring and storing the data. Finally, the data is ready to be refined, so as the data-driven decision-making.

Data-driven decision-making is a powerful tool that can help businesses make informed decisions that drive growth and process improvement. By leveraging data science, businesses can gain insights into customer behavior, market trends, and other key business metrics that can help them make better decisions. For example, a business might use data science to measure the speed of rotating equipment in their manufacturing plant to identify the average capacity of the facility. By analyzing this data, businesses can optimize their production processes and improve efficiency. This can help them reduce costs, increase output, and stay competitive in today’s fast-paced business environment.

There are some important parameters comes into play here. Most data work is focused on tasks such as adding new fields to databases, aligning systems, defining metadata, and implementing low-level governance. Those who work with data often struggle to engage the business on these tasks. Aligning all these with business strategy is completely another level requiring an expert. When businesses ask for better data controls, data specialists may lack the skills or business acumen needed to drive an idea forward. As a result, data activities are often disconnected from business strategy and tend to be low-level and short-term in nature. Data activities are becoming increasingly costly so to minimize such risks it is imperative to collaborate with experienced professionals. Even someone from outside of the company would be a better choice.

There is abundance of opportunities in the field of data science, such as analytics, artificial intelligence, data quality, monetization, privacy, small data, and security. Just like extracting oil out of the rocks deep into the earth’s crust, data needs to be carefully extracted and refined. I would be happy to provide my consulting services and industry expertise to carefully extract things that the eye cannot see—no pun intended!