What Is MIS Really?
In order to understand the complexities of Management Information Systems we have to get the basics of the relevant definitions out of the way. A good place to start is with the word systems, what does it mean really? Simply put a system is a group of components that interact to achieve some purpose. Now, you can see that is a very broad definition and in its context we could literally be talking about any kind of system and is designed to accomplish any kind of task whether it be mechanical, digital, chemical or otherwise. Let's add information to the mix, what is an Information System? It is a system that produces information. Simple right? Not really, we don't really even know what formation is yet! A common view of the meaning of the word information is knowledge derived from data. Okay let's break that down, an information system is a group of components that are designed to derive knowledge from data. That doesn't sound so complicated after all but I think we still need to look at some of the principles in depth to ensure that we have a strong foundation to build our understanding on.
Data Versus Information
Data and information are pretty simple terms but when we are trying to use them correctly and understand their different possible correlations we need to make sure that we really know what they mean at the end of the day. The first thing to know is that without some form of data there cannot be information. Data is simply facts and/or statistics that have been collected usually for some form of analysis. When we are using data to glean information we need to make sure that our data maintains a few characteristics. We need it to be accurate which means we want it to be correct and complete and we ant to ensure that it was processed in the manner we believe. A good way to confirm these things is to cross check the data with other sources whenever it is possible to do so. We also need our data in a timely manner, if we get our data after the information that it provides us is needed then we don't really have much use for the data itself. The data also needs to be relevant in both context and subject. This means that the data is quantified to the level that we need; no more and no less and that it can be applied to our end goal subject. We also want the data to be worth the cost. This means that the provided information must have a greater value than the total cost of the data itself and the processing of it. Lastly, we want the data provided to be just sufficient enough for us to get the information out of it. Any more and it complicates the process of getting the information from it making the job harder and any less obviously means we don't have enough data to get the information we need.
Okay, so we have our accurate, timely, relevant and barely sufficient data that is worth its cost and we know from our definition that we are turning it into information but how do we do that? This part really is simple now that we understand everything else. Let's look at an imaginary earnings chart for a moment. What is on the chart? Information or data? We know from our definition that it is data but when we look at the chart and form an understanding of what that data reveals we know have information! Simply put you perceive data and from it you can conceive information. Looking a little deeper at this distinction we can learn a few things. First, we cannot have information without human interaction with data, it simply isn't possible without the existence of true artificial intelligence. This is an important point because it means that individuals can end up with differing information from the same data if there is a variation in their cognitive skill. This is why a good foundation of knowledge is always important. Finally we now can that it is not possible to send information. Anytime we exchange 'information' in truth we are only exchanging data. That data only becomes information once the other party processes it. All this is important to keep in mid when contemplating the structures and processes that relate to and make up our information systems.
Components Make A System
So all systems are by definition made up of components but when it comes to information systems we can be a little bit more specific than that. A model known as the Five-Component Framework exists and you can see it below.
This model states any information system is made up of hardware, software, data, procedures and people . Hardware being the computers, serves and other machines that are used in the system. The software can be any program(s) used in the system. We know what data is and how it is relative. The procedures are the prescribed process for using that data and interacting with it in conjunction with our software and hardware or the computer side. People are just that, the human side cognitive component that helps us finalize the produced data into our valuable information. This ordered model provides us with some very useful insight to information systems and their management. First of all, it allows for a standardized way to organize and analyze systems. This is especially useful when troubleshooting, designing or even implementing systems. Another interesting feature is that it allows us to visualize workload placement and this can be used when visualizing a system during the design process and analyzing the level of automation and workload distribution. Another insight provided relates to automation. When we move more of the total workload from the right side or human side of the model we are increasing automation and when automation is decreased we must relocate part of the workload from the left side of the model back to the right. We can also see that when it comes to administering the system i.e. making changes, updating and ensuring quality and functionality are maintained we can assess the cost of these actions by understanding the variations of their difficulty. While making changes to hardware or software tend to be seen as an expensive and cumbersome route they tend to be the less difficult changes we can make. The cost of hiring, training, removing people or procedures is substantial as is the effort that is required to do so. This cost ins't simply in terms of money of course, the level of disruption that can be caused in an organization or time lost being productive as well as many other factors must also be considered here if we are going to truly understand the total cost. Our model reflects this reality and shows us that as we move from its right side to the left making changes generally gets more and more difficult.
Don't Forget The M
With all this information we can finally reach the real conclusion of question, what is MIS? It is simply the management of the information system by ensuring that it helps our organization achieve the its strategy. This is first done when the system is designed. We have to ensure we are keeping its purpose in mind and use our fundamental knowledge to do this effectively. Once the system exists in theory it has to be built/produced and implemented. Managing doesn't stop with the first iteration of implementation, we have to keep our system up and running an constantly asses any changes that can or need to be made. Our mission, associated cost, available applicable technology or personnel could change. Any of these changes could force us to make changes to our overall system in order to ensure we keep helping achieve the strategy as effectively and efficiently as we possibly can.These concepts make up the aspects of managing and give us our answer.
The "Laws" Of Tech
There are a series rules that are relative to MIS and can help us keep a good perspective when designing and administering our systems. The first few should always be kept in mind when considering the planned obsolescence of the system or when updates may be needed. Bell's Law states a new computer forms roughly each decade, this has held true since the advent of computers as we know it. Personal Computers tuned into network able machines, then the advent of the internet allowed those machines to talk to each regardless of their physical location and now we can carry new machines with the same capabilities in our pockets in the form of smart phones. Moore's law states that the number of transistors per square inch on an integrated chip doubles every 18 months, this trend has roughly held true since it was first stated in 1965. Kryder's Law tells us that storage density on a magnetic disk is increasing at an exponential rate, even with the advent of flash memory and solid state drives we can still see this continue especially if the size of the drive itself is consider part of the equation. Nielson's law states that high-end user's connection speeds will increase at a rate of fifty percent per year. Why are these things important relative to management? Simple, together they make it clear that our system will never be permanent or always ideal, especially when considering the computer aspect of our five-component frame. Lastly, Metcalfe's law tells us the value of a network is equivalent to the number of users connected to it. This is an extremely important principle to keep in mind during the design phase of our procedures and when considering our hardware/software build. Making our system and its information accessible to more users always has the potential to increase the overall value of the system. These trends of course have the potential to change and vary but the principles that they emphasize will remain true far into the foreseeable future of MIS.
