Data Analysis: Take advantage of the data all around you

Data is passing us all the time in our personal lives, and in our day-to-day at work. Even as you are reading this, there is data being created, it’s everywhere. In the past there was no reasonable way to collect this data which caused, and in some cases, still causes many companies to react to situations created by ill-controlled big data, rather than using data analysis to foresee and prevent situations. 

But what is there to do, using manpower to battle this problem just brings about more of the same problems, not only you going through more money and resources getting better data analyses, but the data analysists themselves are creating data that is sometimes unaccounted for.

Data analysis nowadays is coming into its own, and being revolutionized to a point where if your company isn’t making efforts to sort and utilize raw data and turn it into plans for the future, this very may turn into a case of death by a thousand cuts, just bleeding productivity more and more as time goes by. But let’s dig a bit deeper into exactly what data analysis is, and how we can go about using it to its best abilities.

What do we need to get done?

Now you understand that data is important to gather and understand, we are ready to just get every second and bit of information accounted for, but why? What is the purpose of getting all of this information together under one roof? When it comes to gathering and analyzing data the most important thing to ask are this simple question ‘’what do I want to know?’’. By just gathering data you can end up with some of the same problems that you have without data analysis, only now you have wasted resources to get the data. Helen Mayhew at gives an example of this from her article.

“An organization we know plunged into data analytics by first creating a “data lake.” It spent an inordinate amount of time (years, in fact) to make the data pristine but invested hardly any thought in determining what the use cases should be. Management has since begun to clarify its most pressing issues. But the world is rarely patient. Had these organizations put the question horse before the data-collection cart, they surely would have achieved an impact sooner.”

Looking for the answers to what you want to know is what helps clear away all the unnecessary junk, while all data is important in some fashion, maybe the problems we are wanting to foresee and resolve with the best and fastest results doesn’t require every bit of possible data at this point in time. This opens up the table to making use of constructive meetings to get those questions from our teams through methods of brainstorming and playing devil’s advocate!

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Going from Big data to People  Analytics

While we can use data analysis to answer any question with tremendous results. There is a complete and separate area of big data which is focused completely on people. As we stated above asking the right question is important in any sense of data analysis, this applies to people data as well.

A great example of this would be to look at the total wages of money paid to employees of a certain team, include the paid hours to work, and the tasks needed to be done. This collected data is what I call loose data. It tells us what we want to know, however, there is still so many questions that this data cannot answer. If we dig a bit deeper into more detailed people analytics we can sort out exactly how many hours employees work on each task, how much money was dedicated to each individual task, and any other figure in specific we want to add to the list. Now we have to include the question we want to apply, Are our employees overworked?, Are we making the best use of our employees?, do we need to make new hires? The list goes on and on, what’s important is that we use people data to get a deeper look into the connections between people and data to make the most informed decisions possible.

Dominique Delport asks an extremely important question in his post Big data must become ‘people data’ “What do we need, why do we need it and how do we get it? Start asking people internally (and externally) these fundamental questions. Then find out what sort of data you need to help add value to people’s lives – whether it’s your own teams or it’s the people who interact with your brand.”

By taking all of this data, and using it to discover the answers to what we want to have done. And applying people analytics managers can now do what every company wants in the end, save more money by getting people on the right tasks and minimizing time and resources wasted through losing and rehiring employing. Some examples of this would be.

  1. Reducing wages expense getting the most from your teams

As I touched on a bit above in this blog post, using people analytics can answer the question of, are team members being used the right way? Are my more senior employees being bogged down by lower level tasks? Can lower level workers take on more responsibilities? These are all valid questions when we want to apply big data to people analytics. After answering these questions and sorting out the results companies can expect to see big savings and increases in productivity across the board.

  1. Reducing recruitment cost through improved targeting

Once big data and people analytics gets working inside the company It can be applied on the recruitment process for the company. So that in the end we are just filling a flimsy across the board position, but instead, using big data-driven descriptions of positions that break out of traditional occupational category descriptions.

Data collection in today’s world

We’ve talked about how important it is to take big data, analyze it, answer questions for people data. Gathering data has always been an interesting process. Throughout history, there has been innumerous methods to collect data. Especially worked hours from spy software to the widely used time clock. But these systems are aging as every day goes by they are unreliable and don’t tell us how employees are spending their time on the job, rather it just tells management that they are there. What we have nowadays is much, much better.

Task managers like are making big data collection automatic and effortless. It all starts by organizing out all of the tasks and projects into the system. Afterwards, laying out all the tasks in the order you would like for your employees. By pressing play and pause on tasks the hours worked in every task are automatically logged and preserved on a much more detailed and useable manner that timecards could never offer.  With this information, management can start asking the questions we talked about earlier and get to the solutions quicker than ever, all while killing two birds with one stone, teams are more productive and big data is stored passively.

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But wait, there’s more, as if I didn’t express my love for task managers and big data collection enough. They also take a huge load off our shoulders by making data analysis automatic!  Another form of data analysis is report building, which if you still do this manually, you already know this is a very, very, painstaking process. Not only do you have to burn through resources getting all of the required information together for the report. Add also, it takes time to get all of the data into the systems to generate reports. But, what if I told you that task managers do this for you?

That’s right, task managers not only pool all of that big data for you automatically. On top of this they take the info in organize them into various reports to fill your analytic needs, from people analytics to following resources. What was once a large headache to get organized and sorted out is now automatically generated for you.

Data analysis with has everything you need as a manager to get big data under control and prevent losing money. incorporates data analysis into its very working by giving managers everything they need to use predictive analysis by reading through Gantt charts and highly in depth Time by status reports. boosts output by as much as 25% by streamlining paperwork and thus increasing productivity. Best thing about it is that you can try it for free.

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