Information vs. Knowledge

today what we're going to do is talk about something that Deming thought was quite interesting and I think when you hear it you're also going to find it rather fascinating it's the difference between information on one hand and knowledge on the other what is the difference when I say information and what does it mean when I say knowledge when we talk about information I'd like you to think about this this is a dictionary and it has information in it all it has are words and definitions you really can't do that much with it but it has a tremendous amount of information we use information all the time when we talk about information and when you are sitting in a group you're always sharing this type of information let's take a look at some of the things that you can share one of the things we often do is use antidotes as information I tell you my personal experiences now this might be something that's useful it may be something that's not useful if you listen to groups of people at a meeting you'll find the antidotes are used almost all the time I bet it makes up half of the information presented at meetings now the interesting thing about information that's given us antidotes is that when we talk about antidotes we have a bias our mind remembers the extremes when we're really really busy when we're really really quiet we'll always remember the terrible event we won't remember the time though when we were doing just fine so antidotes are part of information one of the things that's important is that people start talking about antidotes is this quotation the plural of antidote is not data you really can't make decisions based just on antidotes they're useful for getting things started but you can't rely on antidotes the second area that that you can get information from our focus groups focus groups are when you bring people together and you get perceptions of what's going on again you can't run things or you can't implement things just based on focus groups it gives you a perspective that might be helpful in forming plants but it's not going to necessarily change the way your system works the third thing is we rely on data and aren't we inundated with data we get tons of data well let's take a look at the types of data that you might receive when you're trying to make decisions one-pass performance you'll be inundated with information that occurred a month ago three months ago a year ago two years ago that's all interesting stuff but is it able to predict what's going to happen in the future it's interesting stuff but is it something that will make a difference in how we can change our system perhaps some but it's not important from the standpoint of how we will proceed just based on past performance there could be so many variables as to why things happen that way that those variables could change the other thing is we use experiments experiments are great for science is finding new knowledge you have a control group and you have a group that has the experiment with one variable again you might learn something about it but systems are much more complex you can't control one variable benchmarking benchmarking is a way of going out and comparing yourself with other companies or other organizations you find out they're doing really really well and you're maybe not doing so well and consequently you think well I can just copy them and then I'll be able to be just as good again Deming was very very tough on benchmarking he didn't approve of it at all he thought well it's wise to look at their processes because that might help you but he felt there was big differences between groups and maybe the reason why that group is doing so well has nothing to do with how you would do so well he was much more interested in continuing improvement and finally one of the things that's often used is percentages when you're getting data as soon as you see a percentage in any type of data be cautious just remember those denominators can really be quite small and consequently the percentage difference is quite large so be careful when you're seeing percentages so that's the type of information that you're going to receive now Deming would point out that by looking at all this information and such you might learn a few things but it's not the way to manage your system the way you want to manage system is to use knowledge when Deming talked about knowledge he used an example involving a rooster what did he mean by talking about knowledge when you talk about knowledge that has two characteristics it's different than information the two characteristics are one that it's able to be predictive we're going to be able to predict the future if I know something I know what the future is going to be all right for example if I drop something I know it's going to hit the floor that's knowledge knowledge is different than information information doesn't necessarily predict anything knowledge predicts the other thing about knowledge is its theory knowledge is only as good as your last example it can be changed in a minute and that's where Deming used the rooster and he used the example of the rooster in the following way this rooster had knowledge the knowledge was that every time it would go out in the morning in the dark it would go cockadoodledoo and when he did that the next thing that happened was the Sun came out so every morning rooster would go out cockadoodledoo the Sun would go on and so the rooster knew that if it kakadudude the Sun would come out it had knowledge now the interesting thing was one day the rooster didn't go out and the Sun came up the rooster then realized that his theory was wrong its knowledge actually improved its theory was stopped and was able to develop a new theory well I have no control over the Sun so it is with systems we're able to predict and we use a theory we continue using that theory until we find things that happen then they can say we need to discard it and then we develop a different theory that's probably more sophisticated a more applicable that's what knowledge is now as Deming talked about and he looked at all the things that are going on in the system he said some things that were rather scary he said that the most important thing that you need to know about improving your system is unknown and unknowable there's no data for it what a profound statement all we can do is theorize along and continually improve over time and that's where he talked about using knowledge over time to improve things and the thing that he developed was something called a PDSA cycle and at this point what I'm going to have is Ramone is going to talk to you about the PDSA cycle

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