Using Information

How data can be transformed into useful information

How data is used within a company

Data is constantly being gathered by companies in some way or another whether it is being gathered by the company itself or being bought from another organization. This data can then be transformed into useful information which can be used by the company in a variety of ways.

Data can be converted into information by analysing the data for anything that can be useful. That data once identified can then be converted into a easy to understand format. The data would then become useful information that can be used by the company.

Different information is used by different parts of a company. In the case of a marketing team within the company they would want to collect information on their companies clients and target market. This could help them decide on how they should market their products to their prospective clients. For example if they identify the target market as software companies they can collect data on what works well when marketing towards them.

The data that a sales department within a company would collect would be completely different to the data the marketing team would want to collect. The sales department would want to collect data on what products are selling well and trends in the market to predict will be successful in the future. This data can then be analysed and converted into useful information that could be used to decide what products or services the company should produce next.

Another department within a company that would collect data could be the manufacturing department. This department would collect data on manufacturing techniques and equipment so that they can keep up with the competition and stay competitive. By collecting data on new manufacturing techniques and tools and how they would help can help make sure that they are always keeping up to date and using efficient processes.

What is good information?

There are a number of characteristics that define what good information is. These characteristics are:

Valid Data

If data is valid it means that it is correct. You must make sure that all data you collect is valid to make sure that you don't make any errors or base important decisions on incorrect information.

An example of this could be finding some data that says 80% of the population is female. This could lead a company to produce products aimed entirely at women as they make up most of the market. However this statistic is untrue and as a result the new products would not have nearly as big a market as was first predicted.

Reliable Data

Reliable data is data that can be trusted and comes from a reliable source. You would know for certain that data is reliable if you collect it yourself or it comes from an organization that you trust.

An example of collecting reliable data could be going out and interviewing people yourself to get the local peoples opinions on a particular matter.

Timely Data

Timely data is data that can be collected in a timely manner. This means that it will not take too long to collect and will still be relevant to the project when it has been collected.

An example of this could be collecting market data before the release of a new product. If the data is not collected before the product is released or the advertising campaign finishes then it would be useless.

Fit for Purpose Data

When collecting data you must make sure that it is fit for purpose. This means making sure that the data is relevant to what you are wanting to use it for.

An example of data not being fit for purpose is if you wanted to collect information on popular car models in 2015. If the data you collect is from 2013 the data would be irrelevant and not fit for the purpose you need it for.

Accessible Data

Collected data must be accessible. This means that it can be used by others easily and quickly. This would mean that the data is formatted in a way that is easy to read and understandable by the person trying to access it. Keeping data accessible is especially important if you plan on selling that information to other organizations as they must be able to access that data in a quick and easy manner.

An example of this could be if you wanted to use a set of data in a series of calculations. If the data isn't easily readable then it will be difficult to isolate the data you need for the calculations.

Cost Effective Data

When collecting data you must make sure that is cost effective to do so.

An example of this could be buying information from an organisation on marketing statistics. If the projected profit increase from having access to this data does not exceed the cost of buying the data then it would not be cost effective as you are making a loss.

Accurate Data

It is important that the data you collect is accurate so that you know any decisions you make based off of it are well informed and as accurate as possible.

An example of accurate data could be the price of some equipment. If the price is inaccurate then you might not be able to afford it. This would be especially problematic if the equipment was something that you needed.

Detailed Data

When collecting data you must make sure that it is sufficiently detailed for what you are wanting to use it for.

An example of this could be collecting data on cars in general when you need to collect data on only car engines. If the data collected is not detailed enough to include data on the engine then it would be useless to you.