Learn How to take Analytical Decisions from Google
Bangalore: Whatever is discussed about Google, certain facts about this Tech giant are clear. Google is a fact driven decision making company which is specialized in Internet search, cloud computing, and advertising technologies. Its main goal is to organize the information collected from the world Business Intelligence to a great extent involves collecting data and using it to make smarter decisions.
Bernard Marr discusses an example of how Google applies the fact-based decision making from the HR department on SmartDataCollective.
As the Executive chairman of Google, Eric Schmidt said, “We run the company by questions, not by answers. So in the strategy process we've so far formulated 30 questions that we have to answer. You ask it as a question, rather than a pithy answer, and that stimulates conversation. Out of the conversation comes innovation. Innovation is not something that I just wake up one day and say 'I want to innovate.' I think you get a better innovative culture if you ask it as a question”. Google runs on questions. Unlike other companies which runs on collecting data to provide answers to their queries, Google’s aim is to start with questions and be clear about the need of the information. This is clearly a strategy which needs to be lauded for its efficacy; certain times project managers are so overwhelmed with information flooding in from all sources that they just do not take any action at all. In situations like this, they need to evaluate what questions will lead them to their desired output; this will automatically highlight what data they need to analyze.
The Oxygen Project
Google started a group within the organization known as Information Lab with the aim of conducting innovative research that transforms organizational practice within Google and beyond that. The team took up a project named Project Oxygen to answer the question 'Do Managers Matter?'
Which data to use?
The team first had a glance at the previous data and employee survey reports. The information was then placed on a graph to check which managers were good. But the data didn’t help in showing a huge difference; so it was decided to divide the data into top and bottom quartile.
There was a big difference between the two groups in terms of employee satisfaction, turnover and team productivity. However it was found that the teams with good managers were showing great performance.
What makes a good manager at Google? Answering this question would provide much more usable insights.
Collecting Fresh Data
The next question which was asked was, What makes a good manager at Google? The answer to this was by finding new data. The first thing was 'Great Manager Award' using which all employees could nominate managers whom they feel are good. The second came from interviews with the managers from each of the quartile. Based on this data the team extracted 8 top behaviors of high scoring manager and 3 reasons where they are struggling in their role.
Google wanted to share this outcome with relevant people but only sharing was not enough so they followed some actions on these analyses like introducing new yearly feedback twice, continuing the Great Managers Award and revising the management training.
This is another stellar example of how BI is being leveraged to improve performance within the company.
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