InsightData driven decision making
Data driven decision making is supported for technology’s place in many decision-making scenarios. Computerized decision support systems can deliver a competitive advantage to businesses of all sizes from improved efficiency and accuracy, better resource management, cost savings, and increased profitability to name a few. We invite you to discuss with us the opportunities to streamline your business processes and incorporate automated decision-making technology. The future is high-speed, competitive, and attainable.
Data Driven Decision Making
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 data 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.
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.
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.
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.