Himanshu Singh.

SWAG i.e. scientific Wild-Ass Guess is a terminology often used for instances when estimates / decisions are made from general logic or assumptions. These assumption / decision are often made by experts or senior stakeholders from past experience. These decisions some times backed by recent instances / data point estimates (generally samples), though they are all in words. SWAG is unavoidable within organizations considering, firstly, scientific assessments through appropriate data require efforts and time which is not always possible in all scenarios. Secondly, they are mostly made by senior stakeholders who may not prefer scientific data assessment all times.

Time Series Analysis is the kind of trend analysis for for data points observed on a regular time interval. As this technique helps in understanding the past trend of data points / behaviours being observed, we can also predict the forcast of same data points considering all other factors remaining constant / minimum change. It is of very high relevance when we need to refer past performance and predict / plan our future actions considering no major policy change / external factors change. Example we need to predict our people capacity i.e. average people present in office on a monthly basis, by monitoring number of leaves on monthly trend for past few years. Time series analysis can help predict through seasonal variances for a longer time and understand people taking more leaves during DIWALI or End of Calendar year, hence less capacity is predicted on intervals. If we need to predict number of calls / request in a BPO from clients by reviewing count of calls / requests recieved on a monthly basis. This cannot be done through Time series analysis as external factors majorly influence month on month behaviour of the data, hence Time series analysis / seasonal analysis will not support or provide better outcome.

As the term explains flexible staffing, the top criterias to allow / support this method are: - Demand & Capacity : High visibility on Demand & Capacity model is required to understand and predict the demand and deployment of the right individuals (who are cross skilled). Like when a process is on high demand then only addional staff is required to support. - Skill Matrix : Staff should be skilled on cross funtional processes, this can be managed by creating and managing Skill matrix of the staff. Support provided by the additional staff (Cross functional) does match the skill set for the particular demand. - Calibration & Knowledge testing : Calibration of the cross skilled staff to be auited on timely basis to ensure output. As they might forget process / steps during the course of non production within that process. - QMS & Documentation : strong QMS system to support the staff on reference guides and SOP to ensure updated process steps & details are being followed. New requirements might have built in a more vibrant process.