When firms consider analytics and insights, internal data is typically the very first place they go to. They shouldn’t, however, disregard the abundance of information that can be extracted from external and third-party datasets.
Data about your own activities, like operational performance, productivity levels or even sales transactions can help you understand what has happened in the past and predict what will happen in the future.
On the other hand, External datasets or information sources can help you figure out what your competitors are up to, as well as how tendencies like customer behavior, market dynamics, and even the weather might affect the performance of your business activities.
“If you want to take advantage of the transformational potential of data and analytics, you need to be able to understand both i.e., Internal & External Data”
Why is External Data Becoming Important?
Ai/ML solutions, driven by data, are rapidly transforming numerous sectors and marketplaces.
But, not every single company out there has the resources or the technical know-how of Amazon or Walmart, which enable them to generate massive volumes of confidential, internal data from millions of customers.
In such cases, External data can become quite handy and the good thing is that it is readily available to just about anyone.
How did External Data Improve Big Data & Analytics?
Many of the previous data-driven models used by enterprises to forecast demand or changes in supply/demand became redundant overnight during the Covid-19 outbreak due to rapidly shifting behavior.
A huge portion of the internal data on which organizations were dependent was no longer useful.
During this time, businesses discovered that external data was crucial to developing new models for predicting how individuals would react to changing conditions.
Data on internet search activity was especially useful for tracking the virus’ progress, anticipating where behavior changes would be the most severe, and determining what people’s new priorities were in a changing world.
Where can you get External Datasets?
There are many publically accessible external data sets. For instance, many governments make a wide range of data available through portals like data.gov and data.gov.uk.
Alternatively, you can turn to privately held information that is offered free of charge or for a small fee:
Google’s trends and basic search-related data are some of the freely available external datasets. On the other hand, organizations like Experian gather huge troves of data that include demographic and/or marketing data which they pool for a variety of data sources. In addition to this, there are a handful of niche data collecting agencies that offer custom external datasets for various industries.
How did External Data help companies in the past?
- Finance and credit card businesses have been leveraging external data from credit reference bureaus to analyze the risks of lending to individual clients on an industry-wide scale.
- Real estate companies also utilize public property sales statistics to assess the worth of the homes they buy, sell, and lease.
How is External Data Improving the Digital Twin?
External data is redefining the way organizations build and leverage the Digital Twin.
A digital twin is a computer-generated model of a company, a product, or a process that may be used to anticipate how certain factors will influence the performance, productivity or other KPIs in the real world.
While internal data is typically utilized to create the “twin” model, external datasets can also be used to recreate the “environment” in which the twin exists.
For example – Leveraging data from its production processes, a leading vehicle tire manufacturer generates virtual simulations of its tires. It then creates realistic scenarios using external data sources on the road surface condition and its structure, as well as weather data, to assess the performance of new tire prototypes.
Overcome these Challenges to Leverage External Data
Leveraging external data has the potential to be incredibly beneficial if your firm is able to put initiatives in place to manage challenges which include:
- Increased reliance on the external data provider
- No control over the quality of data
- Multiple data sources mean complexities in formatting
- You might need to hire a specialist to clean multiple data sources and format them according to your business needs
However, if you manage all this then it will mean that your data and analytics strategy is no longer just about “you,” but also about developing an understanding of the operating conditions and ecosystems in which your company operates.
It can help you optimize and improve efficiencies across your existing business models, or it can help you change and establish totally new ones!