Organizations initiate process automation projects to improve efficiency. There are different approaches and tools to improve the efficiency such as Lean Six Sigma. An implementation of analytic model is another powerful approach to improve end-to-end service delivery process, especially where the analysts and consultants would have to provide a sophisticated analysis as a part of output. On-going automation process to improve service delivery is transforming the job expectations required for these service delivery professionals.
There are generally two main types of activities involved in delivering services. Analysts and consultants spend their time preparing and manipulating data such as downloading reports, cutting-and-pasting to Excel worksheets, etc Another activity is to analyze data and make a sound recommendation to clients.and customers.
It's our main goal to automate the preparation part of work as much as possible so that the analysts and consultants have more time available to analyze data and recommend solutions. Although there are different tools to achieve this goal, I prefer to use SQL and R scripts to automate the end-to-end process.
With proliferation of analytics, another objective is to automate the basic decisions so that the analysts and consultants can tackle more complex problems and let machine to help with a basic recommendation. Once we started contentious automation cycle with analytics, we can overlay more sophisticated analytic models easier such as deploying a time series analysis and/or optimization algorithm within the service delivery process so that even a sophisticated recommendation can be delivered in a fraction of time. Once you start this cycle, it's impossible to stop. As a result of analytics based process improvement, we now expect additional skill sets from these analysts and consultants.
Analysts and consultants used to be an expert in the business domain and that was enough to be successful. The new environment still requires them to be a domain expert, but we now expect higher skill sets from these professionals. Many of them are expected to contribute in creating an analytic model. More we automate, more time is freed up to help develop next generation of analytic models. This change in how we improve capability requires the analysts and consultants to learn a programming language such SQL and R on top of the business domain knowledge that we require from them. They are also increasingly expected to have knowledge in statistics and other mathematical algorithms as we create more sophisticated predictive and prescriptive models to improve service delivery capabilities and stay ahead of competitors. A descriptive analysis is no longer sufficient.
Things have changed so much, say, in last 5 years. Once organizations decide to embrace the continuous process automation with integration of analytic model to improve both process efficiency and service delivery capability, the job expectations for these professionals must also be changed.. Although the automation is not going to replace work for those individuals eager to learn and move up the food chain, there may be limited opportunities for those individuals fail to embrace the new environment and skills necessary to succeed. Whether you like it or not, analytics is going to play a major role in how we transform service delivery and, I believe, this change will profoundly impact the hinging decision as organizations demand additional skill sets from analysts and consultants.