Overview
A client presented us with their need for streamlining their high volume of maintenance service requests. They were processing these requests by manually searching their database for contractors on a nationwide scale. Although functional, they were interested in a more efficient alternative to their current approach that relied completely on manual efforts for decision-making. This illustrates many of the monotonous tasks that are better suited for automation to free up staff and improve productivity.
Technology driven decision making is the process of using technology to create data–driven decisions. This type of decision–making relies on the analysis of data to identify trends and patterns, which can then be used to inform decisions. Technology–driven decisions can be used to inform decisions relating to a variety of areas, from marketing to operations and beyond.
Many day-to-day business decisions that are manual, routine, and repetitive utilize variables that technology can employ to automate and advance these processes. Current technologies offer an extensive list of capabilities for business process automation to streamline these decisions with speed and accuracy. Implementing technology driven decision-making yields consistent outcomes that establish a standard for your business processes. In turn, this fosters a rise in customer satisfaction, customer base, and ultimately the bottom line.
Approach
We initiated this project with an assessment of the client’s current software, analyzed their workflow, identified inefficiencies, and developed a custom solution tailored to their specifications.
Today, this client’s system automatically decides which contractor is best suited for the service requested. Automating this process saves several minutes per request in contrast to manual processing efforts; multiply that by thousands of requests and that translates into a substantial savings of resources.
The technology used for data–driven decision making can vary, but typically includes techniques such as predictive analytics, machine learning, artificial intelligence, and natural language processing. The data gathered can include customer data, financial data, operational data, and more. This data can then be analyzed to identify trends, patterns, and correlations, which can be used to inform decisions.
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Conclusion
Many businesses are not unlike this particular client; they make routine decisions utilizing the same set(s) of data and criteria. That logic is what fuels technology driven decision-making. We were able to leverage existing data, machine-learning algorithms, and analytics to identify the patterns in their historical data and manual decision-making to automate their service request process.
Technology–driven decision making can be a powerful asset for businesses, allowing them to make decisions based on real–time data and analysis. It can also help businesses identify potential opportunities and risks, as well as optimize operations and processes. Additionally, it can reduce the amount of time and resources required to make decisions. Overall, technology driven decision making can benefit businesses of all sizes, helping them make informed decisions based on data–driven insights.