Using Information

Unit 3 Assignment 1

How is Data Used? (P1, P2)

When collecting data for a company, there are certain specific functional areas that need to be concentrated towards, so that they can they gain data from the information.

Marketing departments are there to advertise the company. The data they will collect will be based on how to advertise their company. They can gain both primary and secondary data for this to see what the best marketing strategy would be to get the consumers eye on their product or products. The information they gain will be transferred into data, and from this they will be able to see what the best advertising is that they used, that has the biggest impact on consumers that will make them want to take interest in what they have to offer. They will do this by seeing how many new/existing customers will take interest in their products within a certain time-frame. They can then also ask consumers directly with questions such as "how did they find out about the company" and what did you think of advertising" obviously using closed questions for that.

The purchasing department will be in charge of the items that they will buy for the company; this includes essential items and sellable items. The information they collect will be based on the items they sell, mainly, since they will need to see how well an item is selling so that they can then use the data to see what sold best and when. The purchasing department will receive the items the manufacturing department needs, they will then use their data that they have collected to see which group offer the best product per pound (£).

The manufacturing department will collect information based on the product they receive. They will then use this information to create data on how well the product is for example. They will be using primary data for this since they won't be able to source any other data from anywhere for secondary. So sourcing their own data will have to do fro this. They will use the information as data to compare to other materials to see which one turned out the best compared to the others that they have received. They also need to communicate with both the finance and purchasing departments to see what they need more of, whether that's selling a lot of one specific item, or not selling enough of the other, they will then collect this data, and send it to both of the other departments so that they can then work out what they need and don't need.

The finance department will be the one that takes charge with the money that is spent in the organisation. This department will be working very closely with manufacturing and purchasing so that they can get the best possible information so that they can then use the data to see where more spending can happen and where they need to hold back on spending. This data will be primary quantitative data as they will need to see vital numbers to see where spending needs to happen and where it doesn't.

The administration department will be the ones that deal with all the paperwork, making sure that consumers are getting their relationships with the purchasing and finance department. The information that the admins will be collecting may well be qualitative data, as their will be a lot of paper work that has descriptions about what the customers want and who they need to be guided towards etc. This data will also be primary since they can't exactly source any other data about customers from anywhere but the actual customer.

The personnel department will be the ones that keep track of all of the staffs data. The information they collect about the staff will be both qualitative and quantitative data, since they will have descriptions about the employees personal data and how much they should be earning for that week, or month depending on how they get paid. They will be sending some of this data to the finance department so that they can then make sure that they are being paid the correct amount, this will also be put down as quantitative data.

The sales department will be the department that will take a lot of information on what has been sold. This may contain both primary and secondary data to see what is selling better in different areas and how much they sell in one month compared to another. It will all mainly be primary data as it will all be figured through amounts so they can send to the finance and purchasing departments.

Qualitative data is data that has a lot more description in it compared to what quantitative data has. This data has more depth into the information that is collected, but is less straight forward because of it's descriptive data.

Quantitative data is data that is made up of numbers. This data has no description and is all meant so that data can easily be picked out so that a business or person can calculate what they need to without having to trawl through a lot of words.

Primary data is data that is made up by that person or business, it is information that has been collected internally by the people that work for the company. It is also good as the data will now directly link to the company.

Secondary data is data that is sourced from many places, this includes the two mainstream sources, books and the Internet. Secondary data can be used to compare that companies data to their own to see what their sales are in different areas for example.

What is good data?

In order to have good data, you have to have many attributes towards the information you are collecting.

Having validity in your data is one of the steps to having good data. Validity is making sure that the data is actually referable to the real world. That what has happened can actually happen in real life and isn't based off of a simulation of something in order to get that data. For example, when virgin media run their tests for the real-world speeds of their Internet, they need it to be valid, that's why they give certain figures of speed for different areas, they will also give this information out, and since it's not done in their own building but in standard homes where people live, that's what makes it valid.

Having reliable data means that you can get the same results each and every time. This will make the data very good as, if you are getting the same information each time when doing whatever it is, then that means the data that you are collecting is reliable. For example, Virgin media will need to test their Internet speeds before they make it public to a certain area, as long as they can get the same speed when ran at the same time of day with the same amount of traffic, then that is reliable data.

Having timely data is also another step to having good data. What this means is that the data you collect can occur at a favourable time, so if you are wanting to repeat something in order to get information, it needs to be done at a certain time in order to call the data timely.

When data is described as fit-for-purpose, it needs to be complete, it needs to be unbiased and it needs to be plausible and accurate. This means that the data will make sense, and that the data is not from people who love or hate a certain brand. It also means that all of the data that can possibly have been collected is available here, and that it is all in full.

Having accessible data, this means that it is available to those that either need it or those that request it under the "Freedom of Information Act". Having good data through this is showing that the company have nothing to hide and the data that they are collecting is true and that they are ready to show that. It means anyone who wants to see the data is able to request it and obtain it. For example, Virgin Media will have specifications for their broadband of different areas on their websites or databases, customers will be able to obtain this because of the FIA, which will then show them what speeds they should be receiving depending on their plan or area.

Having cost-effective data is also a way of having good data. This means that when the information has been collected and when looking at turning it into data, there needs to be a cost effective way of doing this without spending too much money just to see what data you have gained. Having an effective system of gathering the data will make the data good as they haven't spent a whole lot just trying to gain data.

Accurate data, this means that the data that is collected has to relate to what it's trying to show in order for the data to be good. If the data is not accurate, and is not what the real results should be, then the data cannot be classed as good data as it represents nothing. For example, Virgin Media's data needs to be accurate enough that people won't think their service is rubbish because they aren't receiving the speeds they're meant to be, so they need to make sure that the data they collect is accurate for that area and that speeds can vary depending on time of data and traffic.

Having relevant data will make the data very good. This means that the data will link to what it is trying to show and that it isn't trying to show something else that does not make sense with the current context. Without the correct context, it would be confusing to the customers. For example, if Virgin Media where to release their data on Internet speeds, and it shows data on how good call quality will be in that area, that's not relevant, or good data.

Having the right level of detail in the data will make the difference between good and bad data. When thinking about what needs to be included in the data, to expand on what's already there so the customer understands what they are being shown, needs to be really thought about. There needs to be something there that will show them what they need to know and what they don't need to see is data that has been waffled on, that there are pages and pages of one little piece of data. For example, Virgin Media will out some description about their Internet speeds in different areas, if they were to waffle on too much about that speed or this megabytes a second, the data could seem a little bit too much without getting to the point of other data.

Having a reliable source of data is also a way of making your data good or bad. The data does need to come from a source that is known for having high quality information, a reputable brand for example is a great place to start. But trying to gain information from a teenager, would not be a great idea.

The data needs to be understandable by the user, it needs to make sense so that even those that don't understand much about whatever the context is, understand about what is in front of them. If there are pieces of data that aren't marked and shown exactly what it is, or are too brief, then people won't know what it is they're seeing.