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 Q: What’s the difference between “OutPut” and “Outcome”? Aren’t they Interchangeable?

A: The difference between an ‘Output and ‘Outcome’ is significant. Processes deliver OUTPUTS (in other words, what pops out of the end of a process is an output). Here’s an example: The Process = Design a bicycle. Output = A bicycle. An OUTCOME, on the other hand, is a level of performance or achievement. It may be associated with the process, but outcomes imply quantification of performance. Back to our bicycle for a moment: Output = A bicycle. Outcome = More muscle mass. Because it’s about performance levels, you can’t get your hands on an Outcome. (But you can draw it on a graph!)

Why should I care?

If you’re working with a customer to improve their organization or performance, you need to know the difference so that you can describe the ‘outcomes’ you want to achieve. Furthermore, you need to quantify those ‘outcomes’ and track progress over time in order to determine what processes were successful. Simply put: outputs impact outcomes. They are managed differently as well.

 

 

The mechanism for managing outputs and outcomes is clear – projects deliver outputs, programs deliver outcomes. A project delivers one or more business outputs whereas a program is implementation of a set of related projects and activities in order to deliver outcomes. Below is an illustration of the strategic context of benefits realization within a program (with an example).

 


 

There are multiple databases, with transformation of the data between them and the continuous changes made to the data transformation logic has led to the actual system being very different from how it was originally documented. Various business rules can get lost if there is no single version of the truth maintained. The business needs a better picture of the database, the business rules and the transformations in order to initiate changes in the future in an orderly manner. Power Designer is a great tool to bring to light the present state of the enterprise system and show all the business rules as well as dependencies between the various databases.

Using an ODBC connection, a Power Designer can connect to the databases (SQL, Oracle etc) and reverse engineer all the tables, relationships and dependencies into its local workspace. This reverse engineered model is called the Physical data model (PDM). The business does not need to see the technical name or structure of the tables and the various fields or attributes contained in those tables. Hence Power Designer has other models available to depict different levels of detail and functionality. These are the Logical data models (LDM) and the conceptual data models (CDM). The CDM is the graphical representation of the system; it helps you identify the entities important to the business, its attributes and the relationships between them. The LDM is similar to the CDM but has more details with respect to the resolution of referential integrity as well as many relationships. Using the PDM we can generate the Data Definition Language or “DDL” which defines the schema for a database.  The business fairly technical user’s not actual end users can look at the CDM and get a better understanding of the overall system. For the actual business users there is another model available in Power Designer called the Data Movement Model.  This model provides a global view of movement of information in the organization. You can see which database the data is coming from, how it is transformed (including ETL and data replication) and which database (or excel or flat file output) is it being stored to.

As part of the data discovery process we have to collaborate with the owners of each of the databases and obtain documentation about the data flows in and out of the database.  Being an enterprise wide effort and keeping in sync with the concept of showing results to businesses quickly. The approach adopted is to tackle on information flow at a time. It’s relatively easier to try and figure out at one time what is happening to say the item streams instead of trying to figure out what is happening to the item, customer, and vendor all at once. The Power Designer Portal is a quick way to make information available to the businesses. The business’ users can see the data models as we build them and can leave their comments for a particular model.

 

The NBA playoffs are quickly coming to an end. The other night the Miami Heat tied the series at 3-3 with the Boston Celtics to bring it to a game 7. The winner will go on to play the Oklahoma City Thunder. Recently we finished our first Data Visualization class at the University of Cincinnati and the course was a great success. We had 45 students work very hard in a short period of time and I was very impressed as I watched them progress, learning the basics of data visualization, moving to interactive visualizations and ultimately creating their own Tableau Viz for their final project.

The visualization below was created by 3 students at the University of Cincinnati, Dilip Kotlapati, Swetha Vemuri and Sanghavi Iyer. The students did not have much exposure to Tableau prior to taking this class and they created this visualization in just a few weeks. With their permission, I’ve adapted their Tableau Viz into Tableau Public so that I could publish it out.

The “Game Summary” tab embeds an Excel chart that they created and some images, team logos and scores to create a nice summary page of the game. The “Game Details” tab uses an image of a basketball court and the students plotted the game on the court with x/y coordinates and color coding the various types of shots, misses and assists. They made it interactive, one of the requirements for the final project, based on selecting players, teams and quarters. While there are certainly ways to improve this visualization, it was great to see what the students learned and were able to accomplish in such a short period of time.

 

One of the great tools for creating reports and dashboards is the bullet graph.  This type of graph was invented by one of the great experts in the data visualization field, Stephen Few.  If you are not familiar with his work then you should check it out at PerceptualEdge.com.  Bullet graphs are great tools for showing lots of information in a small amount of space.  They allow easy comparison between an actual measure and a target, for example actual revenue results to forecast revenue.  They are very useful for any performance measure against a target.

An easy way to show actuals to a target is a simple bar chart with the addition of a target line.  I would highly recommend using these, but this type of chart is really only useful if the target measure is identical across all performance measures.

Here’s an example of a simple bar chart with a target line.

The above example is a great way to show categories against a single target or average.  You can see other examples on our Blog (The Bureau of Labor Statistics Creates and Excellent Graph and Make Category Comparisons Much Easier with these redesigns).  These are all very well done target lines measuring the actual to some target.  However, in the above example it may not be reasonable to ever sell 16 units of oranges.  Let’s say for example the realistic target for oranges is only 9.  In this case the sales team for oranges may actually be superstars and we’re showing them as missing the target by more than any other category.  This is where the bullet graph comes in. The advantage of a bullet graph is that you can achieve the same visualization but at the same time it allows you to have different targets for the different performance measures.

For today I won’t go into the details on how to make them or how to read them.  There is an excellent description and step-by-step instructions on how to build these wonderful graphs at http://www.exceluser.com/explore/bullet.htm.  Instead, I want to provide an alternative improvement that might be useful to users in certain instances.

Typically the bullet graph is shown in one of two ways, values or percent.  Both of these measures can be useful depending on what result is being measured and compared.

Here’s an example of a bullet graph using actual values (using Microsoft Excel). 

Here’s an example of a bullet graph using a percent as the measure (Created using Microsoft Excel and a different data set).

In both cases you have an actual, the thin, dark blue bar.  That is then measured against a target, which is the dark blue vertical reference line.  The three bands of color in the bar are used as tolerance bands. I have found that in some cases you may want to be able to visualize the actual and target as both the value and the percent.  By adding a dual axis you get the benefit of both (Created using Tableau).

One additional note on bullet graphs. I have encountered two issues with using these graphs on business reports.

First, these graphs are not easy to make using the standard tools.  They are not native graph types in Microsoft Excel, so it requires a good bit of Excel skill to create these and requires a dataset for each graph, specifying the various components necessary to build the graph.  In other words, the person building the graph will not be able to simply highlight the data and create a bullet graph.  Tableau is one tool that offers the bullet graphs natively, but this also requires a bit of understanding of Tableau in order to create them.  However, Tableau does allow the user to create them without creating little data sets for each graph.  There is also an issue with creating a dual-axis bullet in Tableau that they are aware of.  This is outlined in the details of How to Create a Dual Axis Bullet Graph below.

More importantly, there is often confusion around the bullet graphs, probably because they aren’t seen or used as much as other graphs that users are used to seeing.  There is a learning curve to understanding what the graph means, how the actual vs. target is represented and more often what the color bands represent and how to interrupt it all.  However, in my experience, once the users understand them they seem to adopt them relatively easy. This is probably true for any new graph type that has been created over the years.

In my opinion, neither of these issues are insurmountable.  There are enough ways to create these graphs, either by using templates, add-ins, or different software platforms, and once you build a few of them it will get easier and easier.  As it relates to teaching people how to read them, I think the benefit of taking the extra time to educate the user on what they are looking at outweighs the complexity of the graph, both in the creation of it and the user’s comprehension of it.  It may not be a quick understanding, but in this case I think it’s worth the trouble.

However, if you are creating a report that will be read by many and there is no way to explain the graph then it may be best to choose a different way of presenting the data. As an example, in some cases the bands are not necessary to tell the story.  If the goal is to simply show Actual vs. Target then having a single color bar may work just fine (or maybe no shading at all).  In this case it’s simply a bar graph with a reference line for the target. Add a label or two and anyone should be able to decipher this.

Special thanks to Kristofer Still for creating the dual axis bullet graph in Tableau and detailing the instructions below.

How to Create a Dual Axis Bullet Graph in Tableau

You need to start with a set of data with actuals and a target.  In this example the target is a monthly sales quota of widgets and we compare this with sales to date.

First you create a calculated field for the ratio of sales to date to your goal.  This creates your percentage for your first axis. (You could just as easily calculate the percentage as a field in your data source and this might be preferable if you are creating multiple bullets for many targets.)

From there the easiest way to get a bullet graph in Tableau is to use the show me menu.  To do this select your sales to date and sales goal fields and select bullet graph from the show me menu.  You now have a single axis bullet.

Now we have to do some trickery to get Tableau to give us the second axis.

First you drop the percentage field to the Columns tray.  This will create two side by side bar charts.

Next you drag the percent axis and drop it on top of your bullet graph.

Now that we have the dual-axes there are some additional formatting steps to clean things up:

You want to change the color palette to one of the single gradient palettes and make the percent of goal measure a darker shade and sales goal a lighter shade.

You should also change the formatting of the top axis to percentage.

There is also a bug in Tableau that you will notice.  The reference line for the goal of 10,000 units doesn’t cross at 100% of your top axis.  Tableau provided me with a fix for this.  If you set the axis ranges proportional to one another then they will line up.

So in this case if you extend the upper end of the range of the percentage axis to 1.05 this will cause things to line up.  Be careful, though, this axis is now fixed and won’t automatically update if you place the bullet on a dashboard.  This is less than ideal, but unless you have wild swings in the magnitude of your measures you should be fine.

Your final bullet will look something like this:

Data Tables are great tools for adding context to a chart or graph for data visualization. As an example, in the redesign of the Hamilton County Auditor’s chart the addition of the data table at the bottom of the chart provides detailed data to augment their compelling story. See “Design Issues Distort a Compelling Story for the Hamilton County Auditor”. However, be careful when using these data tables in Excel and remember to always check your data!
Below are 2 columns of data. Column A has a date and column B has number of units.

 To create this simple line chart with this data and add a data table:
1.) Highlight cells A1:B5
2.) Click “Insert”, select “Line” and then select the first 2-D Line Chart option
3.) Click “Layout” under Chart Tools, select “Data Tables”, then select “Show Data Table”

By default the chart will look something like this:

After some chart clean up and reformatting, the chart looks like this:
Data labels added to showcase the discrepancy between the actual data and the data table values.

Excel automatically treats the dates in the proper order, from September to December. Also, the line chart and the data labels show correctly and the values are clearly decreasing at a rate of 100 units per month. However, the values in the data table are reversed. This is not an axis problem and this cannot be fixed by reversing the order on the axis. This is a critical error in the way Excel handles the data within the data table. The first cell, either at the top of vertical data or on the left of horizontal data, will be the first cell in the data of the data table, even if the date are automatically sorted by Excel.

The easiest solution for this is to simply reorder the data by date from oldest to most recent. Once the dates are resorted then the data in the data table will be correct.

In further testing, it appears this problem is only associated with Excel’s “Date” format. If Column A were just a 4 digit year and set to Excel’s “General” format instead of the “Date” format then the data in the data table would match the appropriate year. However, in that case both date and units would be in the reverse order and then the horizontal axis would need to be reversed.

The data table offered in Excel 2007 and 2010 is a terrific tool, but there are some issues to look for when using them. An important lesson is outlined here as well, always double check the output. Always approach the data on the assumption that there could be a problem with the data and never trust the data or any tool to do the work automatically and without error.

iPhone4S

iPhone4S

Like most of you, I recieve a lot of publications in my inbox each day.  This morning, an interview in Intelligent Utility caught my attention.  The interview, IT’s Workforce of the Future, is a very interesting observation by a CIO who has been in the workforce for less than 20 years.  In the interview the CIO, Branndon Kelley reminds us that in 1999 our workplace had better, faster technology than we had at home.  Today, for most, that simply isn’t the case.  We have a new workforce emerging that has been immersed in technology since birth and want to bring that to their new post-college positions.

Branndon issued a challenge for those of us “old timers” in IT.  Certainly our experience has taught us to be cautious and deliberate and to plan our project carefully.  These new techies, however, are more likely to jump in with both feet and more optimism.  Neither is certainly a perfect strategy but their is a lot to be learned from both.  Business is changing faster and faster every day.  When evaluating your projects here are some things you may want to consider:

  1. Is there truly a compelling business reason why I couldn’t move my data to the Cloud?
  2. How can I inspire my technical team to think more creatively and collaboratively?
  3. Why does my staff need a permanent desk at my site?
  4. Can I find the best resources in my town/headquarters?  What if I was not limited by geography?
  5. What tools do I need to get in place now so that I can enable my teams to push the boundaries of location, work hours, and technology?

Food for thought indeed.  How would you respond to the questions above?

- Jodie

 

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For some time now we at LUCRUM have been talking about cloud-based Business Intelligence solutions as a viable market alternative.  We partnered with www.1010-data.com, offering big data – data warehouses in the cloud, and with Ocucue, offering “object” (as opposed to KPI) based data visualizations in the cloud.  Executives from both of these organizations presented at our BI Symposium back in September. 

Well, BI in the cloud just made a big leap forward.  The poster child of cloud companies, Salesforce.com, has now entered the mix.  Salesforce announced a few days ago the availability of www.database.com, a service they (salesforce) will be offering, based upon their existing architecture.  WOW…  The game should start moving even faster now, what with Salesforce now directly competing with the major Database vendors (Oracle and Microsoft specifically).  I personally find it interesting as well that of all the areas Salesforce could have brought to the cloud (vertical/horizontal solutions, ERP/MRP systems, yet another email system, etc) they chose Database.   Oh, don’t get me wrong, it makes sense relative to leveraging their existing infrastructure, but I think it’s an interesting vote on where BI, Data and the cloud are headed.

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At some point in every project, I’m usually confronted with the question – should we build or should we buy?  The pendulum of thought on this topic swings back and forth.  As a consultant that regularly advises clients on these kinds of questions, my current read is that the mindset has moved toward the “buy” side on some key fronts.  The trends underlying this, and their impact on both business and technology, are complex and evolving.

Another way to frame the discussion is, “Has someone already solved that problem?”  When the answer is yes, the existing solutions deserve a good look.  In my experience, a combination of both buy and build often turns out to be the right answer.

Let’s take the issue of getting more out of all that data that has been loaded into your company’s Microsoft SharePoint-based collaboration site.  Someone (probably many someones) has spent lots of time getting thousands of documents, contact lists, project plans, and other kinds of essential data into this amazingly versatile tool.  And if your portal has been well-designed, you probably find it an invaluable resource while you’re using your laptop or desktop at the office.

As soon as you try to get this information out using your mobile device, let’s say using your iPhone, it becomes a different story.  Even if you manage to navigate to the right place, the functional richness of the interface is not ideal when you move into the realm of finger touches and gestures .

So what to do?  Build a new, mobile version of your SharePoint site (probably a tough sell given the current economy)?  Or has someone already solved this problem?

As it turns out, the creators of SharePoint provided a shortcut to get to stored data directly.  This method uses web services – in human terms we might call it the “just give me the data, please ” service – to make the data available without the need to navigate through a web page.  It’s up to the application you’re using to determine how the data should look and be presented.

But until recently, not many people had solved the other part of the problem – taking the SharePoint web services and building an iPhone app to make it useable on a mobile device.

Attache screen shot

A screen shot from Attache, the SharePoint client for iPhone, developed by LUCRUM.

One of our talented staff members, a big SharePoint fan, was also excited about the idea, and he knew how to use SharePoint’s built in web services to get data out.  So he wrote an app for that!

When he put two technologies together (buy + build), it increased the value of the data we already had, by making it more portable and our staff more productive.  Kudos to him for seeing the opportunity and going for it!

A growing number of developers have followed this lead to build iPhone apps that put all of your SharePoint data at your fingertips.  There are several choices now available in the Apple App Store, including (in alphabetical order):

I’ll expand further on some of the topics touched on here in later posts, including more thoughts on the “build vs. buy” decision, the changing dynamics in data visualization, and how business intelligence solutions on mobile devices are impacting the way we work.

-Eric

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eWeek published a video describing the value of using Business Intelligence to find and exploit market and revenue opportunities.  Great point, and very well worth the 6:49 it takes to view it.  Many organizations are using BI to understand some of the basic historical results of their business.  It’s the next level of organization who begins to answer questions like the below using their BI toolset:

  • What are my customer’s buying is a basic question, but moreover, what products do they buy together?
  • Which products do they buy when times are tough?
  • What did they buy during the last recovery?
  • What aren’t they buying, and what should I recommend they buy?

All great questions, and clearly a value add of a strong BI platform.

eWeek – Using-Business-Intelligence-to-Find-Your-Economic-Recovery

“In God we trust; all others must bring data.”
- W. Edwards Deming

At our BI Symposium on May 6, 2010, Jeff Shaffer provided us with great insight on how the way we present our data can be just as important as what we present.  Jeff is not a big fan of pie charts.  In fact he has 4 rules:

  1. Don’t use pie charts.
  2. If you use pie charts, be careful in chosing the number of items you chart.
  3. If you use pie charts, be sure they are “centered at noon”.
  4. If you use pie charts, make sure that they sum to 100%

Jeff shared lots of bad charts, lots of REALLY BAD charts and summed it up with some great looking dashboards. I encourage you to check out his presentation!

View more presentations from Jodie Heflin.

- Jodie

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