Why Aren’t Productivity Gains Being Realized?

In an article on informationweek.com, a “human bottleneck” is referenced, which means that an IT system’s capabilities, which may technically be vast, are often limited by a user’s knowledge, technical expertise, experience, and training.

This suggests that in order for firms to realize the full potential of both their human capital and their IT infrastructure, they must invest in adequate training for users. While this is considered to be an added expense and lost productivity by most, it generally pays off for the firm in the long run and helps them get the most out of their IT investment.

Since new IT infrastructure and processes effectively change the way people work, there is a clear need for re-organization of processes. The problem is that IT is often implemented by IT departments, often without enough input from would-be end users. If the new system is an HR/Payroll system, then high-level involvement from the HR department is essential in assessing the available options, implementation, and roll-out. Companies that had/have difficulties realizing productivity gains usually did not align the IT investment with business strategy and organization.

For example, my firm has a customer care department, whose tools all reside on an intranet. The agents use about 30 different tools to find information about orders, accounts, products, and other customer information. These tools often take 3-5 clicks to access. We took 10 tools which representatives use 80% of the time, and combined each tool’s interface into one web page that was set as their default homepage. This simple re-organization of the IT resources allowed the agents to process about 8 more contacts per shift, which is a 10% gain in productivity.

Problems with mounds of data include important, vital, useful data getting overlooked. When decision makers are simply presented with raw data from transaction processing systems (which may be many separate systems) they may not know how, or have the time to, sift through the massive banks of data.