From the course: Introduction to Business Analytics (2020)

Internal versus external data sources

From the course: Introduction to Business Analytics (2020)

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Internal versus external data sources

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- Did you know that data has surpassed the value of oil in recent years? This means that your organization really needs to do a good job of collecting data. There are limits, though, to the value that you can get out of your data. Sometimes, you need to bring in data from outside your organization. This highlights the distinction between internal and external data sources. An internal data source is defined as information that your organization is generating. One of the most valuable internal data sources you can collect is sales data. With proper data governance, you can create a rich dataset that details your customer's buying behavior. Now the data governance piece is very important here. Since the data is only known to you, this means that all of the responsibility of collecting and managing these types of data sources, all that falls on your shoulders. Your organization also needs to ensure that these data sources are in a usable format. Next, we have external data sources, which is data that is generated from outside of your organization. But you can use this data to better inform your decision-making process. These kinds of data sources can help you get a better understanding of the overall market climate. I like to make the analogy that internal data sources are like the organs of a small animal and the external data source is like the ecosystem that that animal lives in. One situation in particular where external data sources are very important is when an organization is going into a new marketplace. They can buy industry reports to better understand the forces that are at play in their market. If the market is a blue ocean, you can study industries you believe are similar to the market you are trying to expand into. This will give you an idea of the challenges that you might face. Organizations that use both external and internal data sources together gain an advantage in the marketplace. To bring back the animal analogy, it's important for an animal to keep its body healthy, but only focusing on the internal will make that task much more challenging. Animals need to understand the ecosystem, how to hunt, how to not get eaten, when to hibernate, et cetera, in order to keep their bodies healthy. Now let me show you this in action. One of my larger consulting clients sells retail hardware online, which is a hyper-competitive marketplace. They were interested in optimizing their pricing structure in a very interesting way. In their market, customers really only consider two things when they make their final purchase decision, what is the review rating and what's the price. They hired me on to create a system that would web scrape all of their product pages and all their direct competitors' prices pages, too. That way, I could create a database and we could look across each SKU. We mined this database to find products that had a higher feedback rating but a lower price than their direct competitor. The idea here is that if my client has a superior feedback rating, they could increase their prices until they matched their competitors'. We found that their pricing model was under-optimized and they were leaving a few million dollars of margin on the table. This is a great example of how combining internal and external data sources can help you land some big wins for your organization. Now that I've walked you through leveraging both internal and external data sources, it's time for you to start making better data-informed decisions.

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