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The Secret To Keeping Technology Running Smoothly? A Human

18 September 2021
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During the pandemic, we saw a huge influx of businesses go digital. Financial institutions, healthcare systems, apparel, fitness, even grocery stores were all hastily forced to move online. Massive technology shifts took place without much planning. Some businesses made the move and found themselves unprepared for the upkeep and overall management the change required. 

No matter the technology, one thing remains constant: a human needs to be engaged in the work to catch errors and solve the problems automation can’t. Technology might have allowed companies to adapt to the changing landscape during the pandemic, but without the proper human oversight, issues are inevitable.

Half the reason many companies aren’t getting the full value out of technology and software is they haven’t done their homework to know how to best optimize it. Many businesses are trying to solve fast for digital first and can’t. They end up investing in software or technology to help, but without a plan or a strategy in place. This frustrates employees, which has a negative impact on customer experience, which affects the employee experience… and the cycle repeats until something gives.

Companies need to invest in data architecture.

Take the time to do the work. Create a solid foundation as you go digital. The number one priority: Plan and build your company’s data architecture.


Most companies need to start with building a data architecture that is cross-functional. This means aggregating and mining data across departments and from all the different platforms being used, such as CRM data, email marketing data, website analytic data, and customer service data. This data is usually collected and stored in a data warehouse, a central repository of data that can be analyzed to make more informed decisions.

This also includes your tech stack. Identifying key areas of data points that can be leveraged across functions can help with customer journey mapping across the business. Figuring out what data points are necessary for products as customers use them in the first 60 days, 1 year, 2+ years. Those are the data points that need to be actionable and need to be what drives cohort analysis overtime. The most important part: Humans using the data to make better business decisions.

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