The Internet was a big enabler of such automation of data capture. On the surface, it looked like the Internet was just a convenience to customers, but it also enabled easy data capture by the retailer. Perhaps, early on, this advantage was not obvious. In reality, this data capture on websites was implicit in the operations of the website. Operating a website and processing an order required (implicitly) that the retailer have your name, address, email address, and such data. From the beginning this gave Amazon and other Internet giants an edge over brick and mortar stores. For brick and mortar stores to ask for and collect customer data, they had to offer loyalty programs and give up some margin to the customer for participating. Internet firms got customer data just by operating. Customers granted that such data was needed to fulfill the transaction. Internet firms got smarter about this and began to recognize returning customers and auto-populating customer data fields. Amazon, as an example, developed many login conveniences and even purchasing conveniences that allowed users to share their data once and have it recognized automatically forever. It turns out that automatic or nearly automatic data capture was a huge advantage. This enabled a drastic change in the interface between customers and firms.
Today, of course, automated data capture is being made even easier by the next generation of web mining processes that track our every move on a website. With data and lots of it, firms like Amazon, eBay, and Google could create Big Data assets and leverage analytics to find business and economic truths in the data. It totality, it has allowed for automated decisions or other data-driven processes that could even replace humans.
It is important to point out that in these examples, the most critical step is the automation of data capture. Early websites required that we enter data (once). Today, our phones recognize our physical location and automatically respond to it. This ability to capture data with little or no human activation is very valuable. It is the basis for advanced automation and decision processing that will provide advances like the driverless car, algorithmically driven energy grid networks, and even management of cities. It allows for not just a greater capture of data, but also surveillance when we least expect it.
Today, with the expanding use of smartphones, sensors and wearables, implicit data capture is all the more achievable for firms. An important aspect of Big Data creation and the movement to automation will be the automated capture of data. Some important points to consider for your business when automating data capture:
- Leverage implicit data capture from digital platforms like webpages and mobile devices. Being online is not just about selling online, but rather about learning about the customer and gathering new data through a rich customer interface!
- Deploy a network of sensors to get data can is otherwise hard to capture via existing digital platforms. Consider Google with Nest and Progressive with its speedometer on cars, and various health insurance firms deploying wearables for policyholders.
- Make rational decisions based on the data captured and be transparent. Nothing will upset a customer more than to know they were treated adversely and yet not know why. Be transparent with how you will use the data. This will be critical in areas like healthcare.
- Embed data capture in your business processes and operations. Lots of business processes in operations capture information about customers and markets. Leverage that data for insights. Yelp and TripAdvisor and other community sites have made a business out of converting comments and experiences into rich data. It is automated data capture at work.
Professor Walker provides keynote talks, seminars presentations, executive training programs, and executive briefings.
Recent talk topics enjoyed by clients have included:
“From Big Data to Big Profits: Getting the Most from Your Data and Analytics”
“Data Monetization”
“Leveraging Artificial Intelligence and Automation at Work”
“Winner Take All – Digital Strategy: From Data to Dominance”
“Success with an Inter-Generational Workforce: From Boomers to Millennials”
“FinTech, Payments, and Economic Trends and Outlooks in Consumer Lending”
“The World in 2050: Risks and Opportunities Ahead”
Exceptional executive training programs have included:
“Digital Disruption, Automation, Analytics, Data Science, the IoT, and the Big Data Wave”
“Master Course on Operational Risk: Measurement, Management, Leadership”
“Complete Course in Risk Management: Credit, Market, Operational, and Enterprise Risk”
“Cyber-security Training: Prevention, Preparation, and Post-Analysis”
“Managing Your Brand and Reputation in a Crisis.”
“Strategic Data-Driven Marketing”
“Enterprise Risk Management and the CRO”
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