WEBINAR: 5 Ways to Create Charts & Graphs to Highlight Your Work (Intermediate)

Editor's Notes

• #2: Moderator (Tracy) Hello And Welcome to GoLeanSixSigma’s webinar: An Introduction to Lean. I am Tracy O’Rourke from GoLeanSixSigma.com, and I will be your moderator today. Transition: Our presenter today is...
• #7: As you can see, We have Brick-and-mortar, and online companies. there are diverse industries such as healthcare, financial services, manufacturing and government Why? Because Lean Six Sigma is about problem solving, and once you have an organization, you’ve got problems! Like all of you, these companies want to be the best at problem-solving, so you’re in good company Transition: More on some of the benefits later...but first let’s review our agenda.
• #8: Today we’ll use a mini case study to show how charts and data tell the story of an improvement project We’ll focus on these 5 basic charts – they are the most commonly seen in improvement projects And then we’ll give you some tips on how to create these charts and graphs on your own
• #9: Okay read this carefully – it’s full of critical information Okay – now STOP reading! Consider – how many times have you been in this position? How often are you reading an email or a project charter trying to determine what’s important? What is this person trying to tell you? Let’s try a shorter version….
• #10: The Short version is, “6 pieces of dishware break per day on average” I got “ABC It For Me” from a team lead who was quoting his boss – She had no time for long explanations So this team lead had to get into the habit of editing and tightening his work My favorite Mark Twain Quote goes like this, “sorry for the long note, if I’d had the time I’d have written a shorter one.” It’s funny, because it’s true! Editing your emails, reviewing what you’ve put into a Project Charter, that all takes time! If you don’t take the time – then you put the burden on the reader I once had someone describe getting emails back from their boss that said, “TMW” That’s a 3-Letter acronym for “Too Many Words” – funny – and again, true! Let’s consider this same issues with numbers…
• #11: Okay – read this carefully Now STOP! – Some of you are already on to me, but, again, I’m making a point I see this kind of “wall of data” all the time Everybody has spreadsheets of data – but, like text, they take a while to read and decipher We’re going to study the “greatest hits” of charts and graphs to see how they can help us get our point across faster
• #12: Research shows the human brain processes images 60K times faster than text Think about that - 60K times is a lot! When working on a project – your job is to tell the story of improvement Your data provides you with a great opportunity for telling that story visually We’re going to use these 5 charting methods to see how they can help But first, we’d like to hear from you….(Poll)
• #14: First up we’re going to cover the Histogram What’s a Histogram? Histogram are charts that show the distribution of values produced by a process They are visual displays of how much variation exists in a process Let’s look at a basic example
• #15: This is an example – It’s unrelated to our broken dish project - We’ll use this to understand the parts of a Histogram This is often referred to as a “snapshot” of our data In this case it’s a snapshot of time to seat customers in the month of June The X or horizontal axis has the scale – in this case it’s minutes The Y axis shows frequency at each level If we take the shortest bar to the left – it shows that one time, it took 14 minutes to seat a customer So that bar only goes up to 1 on the Y axis You can calculate the range – the maximum (22.8 minutes) minus the minimum (14 minutes) Almost a 9 minute range The other thing we can see is the center of the data – the tallest bar is the “Mode” The stat software for these charts also calculates the median, the mean and other basic stats You can also see the shape of the data – is it a normal bell curve or skewed It’s a great chart since it’s packed with information that can be seen at a glance Let’s get back to our broken dishware – what can the Histogram tell us about that data?
• #16: The original issue was that an average of 6 pieces of dishware break per day We deal a lot in averages – and they can be helpful But your process has more going on than the average Some classic misuses of averages are enlightening In 1984 – Graduates of University of North Carolina starting salary was over $100,000 That happened to be the year that Michael Jordan graduated from UNC and signed with the Chicago Bulls Or – another one – the average diaper wearer is 40 years old – in this case the population is split down the middle – very young and very old – so an average doesn’t work Let’s take a look at the histogram of broken dishes The average was 6/day, but the mode (highest bar) is 5 dishes – and that’s because one day there were 20 dishes broken! Was Michael Jordan using dishes to shoot basketballs? The data is a bit skewed, they seem to break at least 4 dishes a day and that seems like a lot But we don’t know when the 20 dishes were broken – early in the month? Later?
• #17: Another helpful thing about Histograms is when you add the customer requirements Back to our example of seating customers. Everything above 10 minutes is unacceptable to customers You can even change the color of the bars In this chase we highlight everything over 10 minutes to show that they’d be “seeing red” or peeved This is a great way to highlight the beginning of your story – the baseline You want people to see how bad it is so they’ll support you in fixing it
• #18: Now let’s see what else we can learn by showcasing our data with a Run Chart or Time Plot What’s a Run Chart? A Run Chart, or Time Series Plot is a graph that shows data in sequence over time Let’s look at a basic example
• #19: The key is that Run Charts shows what’s happening over time It could be over a day, a month a year or just a shift – the X or Horizontal Axis is always over time The Y or vertical Axis is whatever is being tracked things like time to seat a customer, defects per day, it’s a great all purpose chart The classic center of a Run Chart is the Median half the data or 10 points are above, in this case And half the data, the lowest 10 points are below the median We’re used to seeing Time Plots in the newspapers And you should always have one of your project data You want to see the trends and shifts of your data Is it random fluctuation? Is it going up? Going down? The Run Chart Tells you what is happening over time
• #20: Back to our Broken Dishes project – what can the Run Chart tell us? What is happening to the dishware breakage over time A Ha! – It’s getting worse! The one day that someone broke 20 dishes happened on the last day in November As soon as you have 7 points in a row above or below the median, the process has shifted Time to do some more digging since this is costing the company money and probably alarming the customers
• #21: Run Charts or Time Plots can also show what happened before and after a problem was addressed In the case of the time to seat customers, the team would want to highlight the fact that the time decreased once they fixed the issue There’s a shift here too, but it’s a good one – that’s what you want to showcase at the end of a project
• #22: Now lets’ see how the Pareto Chart can highlight our project work What’s a Pareto Chart? A Pareto Chart is a Quality Chart that helps identify the most significant sources of defects
• #23: Let’s take a a look at an example – this chart shows the different types of food orders The Pareto Chart is for categorizing data In this case the team was categorizing what people ordered out of 100 orders The X Axis shows the categories are Salads, Combinations, Sandwiches and so on The Y axis shows the frequency or the number of each category In the case of these orders, 22 out of 100 were for salads 20 out of 100 were Combinations There is also a second Y axis that shows the percentage And the orange line in the center shows the cumulative average If you add the salad orders to the Combination orders, you get 42% of the total This helps team zero in on the category of highest impact Let’s see how that might help with the broken dishes project
• #24: In the case of the broken dishes, the question is, what are we breaking the most of? Bowls! Out of 188 broken dishes in the month of November 150, or 80% were bowls That’s very helpful since it will help the team narrow the focus of their investigation This chart caused them to change the project scope to just address broken bowls Paretos are great ways to highlight data – they help others see – at a glance –the biggest source of problems They can also be used to dig deeper – lets’ go back to those 100 food orders
• #25: In this food order chart – Salads were the most common order So – it’s even more helpful to the team ordering supplies to know WHICH salads are most popular Turns out it’s the flying fish Waldorf Salad That’s a great feature of these charts One Pareto can lead to anther These are called nested or “cascading” Paretos It requires collecting more data It results in understanding what’s inside the biggest bar
• #26: Next up – we’ll consider the misunderstood Box plot My favorite What’s a box plot? A Box Plot, also known as a Box and Whiskers Plot, is a graph dividing a data set into quartiles and with a center box containing 50% of the data and two whiskers that each represent 25% of the data That sounds like some kind of cartoon cat, so let’s get a closer look
• #27: This chart involves New terms and not intuitive Deals in quartiles – but that just means fourths – you divide the data by 4 Shows the distribution sort of like a Histogram (see if it’s skewed) This still doesn’t quite make the box plot clear Let’s compare it to the run chart
• #28: Now you can see how the box plot divides the data set into 4 Since there are 20 data points, each quartile contains 5 data points The bottom quartile is the lowest five values The top quartile represents the highest 5 values Generally takes a bit of experimentation to get a feel for it This just shows the 2 methods of displaying data and how they’re related We’ve been showing you a single box but this chart is best for comparisons Let’s get back to the broken dishes…
• #29: Back to the case of the broken bowls We can use the box plot to stratify the data by shift Breakfast and lunch experience some broken bowls, but the median breakage and variation is much greater at lunch This begs the question, what’s different about lunch? The box plots are also helpful at showing the outliers – there are those 20 bowls again! With this software it’s a dot In other software packages it’s an asterisk – or multiple asterisks It’s just letting you know that this data point was different from the rest of the data set
• #30: One common method of comparison is to reflect on the process after it’s been improved Box plots are great for showing “before and “after” It’s much easier to compare box plots than histograms since you can get them closer together You can see if the variation was reduced, along with whether or not the median moved in the right direction Again – a great visual to share with leadership that tells your story quickly
• #31: So far – the charts are telling us a story Breakage is increasing over time 80% of the breakage is bowls Most of the breakage is happening at lunch time When asked about this - The staff said the soup and salad special was driving the sales of conch chowder – Hence the use of bowls… And they say the customers keep asking for the chowder to be hotter They suspect the staff is dropping the bowls because they’re too hot to handle Hmm – if we only had a chart that could tell whether or not the heat of the chowder affected the breaking of the bowls
• #32: This last chart helps us to understand if there’s correlation between to variables it’s a great chart to use when trying to prove or disprove hypotheses What’s a Scatter Plot? - The Scatter Plot is a chart that shows if whether there is a relationship between 2 variables
• #33: Here’s an example that is comparing outside daily temperature and Daily Sales Let’s review the part of the graph Scatter Plots require “paired variables” That means there are two columns of data They Y or dependent variable is on the vertical axis The X or independent variable is on the horizontal access We’re trying to see if changes in X, result in changes in Y This graph shows that as the daily temperature increases… The daily sales also increase – seems to be a correlation… Now let’s get back to that hot chowder
• #34: Does the breakage goes up as the temperature of the chowder goes up? YES! We can go watch the waiters and waitresses to confirm, but the data shows a correlation
• #35: Of course – there may be no correlation at all I worked with a team in hotel and they were trying to understand why their staffing model wasn’t working They had always based the staffing in their onsite restaurant on the number of guest reservations for that day But when they compared the reservations to the number of orders, they found nothing It’s only when they removed lunch and dinner orders that they found correlation The number of reservations DID correlate to the number of breakfast orders That Scatter Plot helped them change their staffing model for the better
• #36: It’s official – Conch Chowder is the biggest selling lunch items – along with the sandwich It was so popular they didn’t have enough trays to go around And since they were making it hotter to respond to customers, - Without enough trays, the bowls were too hot to handle Since the Soup n’ Salad Special is not going away, the bistro is investing in more trays Problem solved
• #38: Let’s review: Histogram: - Shows the Center, The Spread and the shape of the data – great to show how the process performs against customer expectations Run Chart/Time Plot: - Shows data over time Great to see if there are trends or shifts in the data Pareto Chart: Shows categories of the sources of defects - Great to focus on the biggest contributor to the problem Box Plot: Shows data divided into quartiles - Great to compare the center and distributions of different strata of data Also great to show before and after improvements Scatter Plot: Chart they shows whether or not two variables are correlated Great to help prove or disprove hypotheses
• #39: This a behind the scenes look You cannot create these charts unless you have the data properly set up The histogram is one column The Run Chart is time based so you can add a date or time column Pareto is just a table with a the category names and their totals The Box Plot could be one column or as many columns as you want to compare The Scatter Plot requires paired data – always in two columns
• #40: T
• #41: These links take you to both instructions for each chart and data sets so you can try them out yourself There are instructions for both Minitab and SigmaXL If you don’t have either, you can get a 30 – day free trial of SigmaXL and see if you like it There are lots of other software packages as well as Excel add-ons They all function pretty much the same way Scatter Plots and Line Charts are easy to make in Excel without additional software Good Luck!
• #42: I hope our visit to the Bahama Bistro helped you see how Charts and Data can tell the story These 5 Charts are basic but have great versatility in what visuals they provide Please visit our website and try these out for yourself – Just adding one chart in place of text or data will make a huge difference in how others view your work Remember: People process images 60K times faster than text – That’s a big difference!