Going Spatial: Creating a Map of Prop 37 Votes

When charts bore you, create a map!

Spatial Analysis is increasingly importantAs I continue my sabbatical, one of the projects I am working on is earning a certification in Geographic Information Systems (GIS).  Why?  For much of my career I have been creating charts… charts showing revenue growth over time, charts showing sales rep performance, and charts showing the health of a SaaS startup.   After 15-years of charts, I felt it was time to explore another form of data visualization.

I enrolled in the GIS Specialization offered on Coursera and created by UC Davis.  I am all too familiar with data transformation, data management, and blending of data, so I was really curious how different a GIS would be compared to the likes of Salesforce.com of Tableau (which does offer mapping).

The Fundamentals of GIS course itself is much more about learning to use ArcGIS and ArcMap.  We did learn about projections, GIS best practices, what spatial analysis really is and how to open the ArcMap software.  Aside from learning the tool and file types, there really wasn’t much different from what I already knew as a data and insights analyst.

Take the final peer-graded assignment for Fundamentals of GIS as an example.  The course provides data including a counties data file defining counties in California.  The course also provides a second data file including voting precincts and the voting results for Prop 37.   The goal is to combine the two data files and create a normalized map showing the ratio of Yes votes to total votes. Seems simple enough?

It was fairly simple.  As with any data related project, the first thing you do is to download and validate the data.  Can you open the zip files?  Is the data there in its entirety? Once you know the data is usable, get to know the data.  Look at the metadata to see what fields are included and what they mean.  Since we have two files which need to be combined, we need to find a primary key to join them.

While it took me a few minutes to review the data, it took a bit longer to understand the connection between the two data sets.  It was clear that we needed to have a one to many join and a spatial join.  There are a few different ways to do this. I first decided to summarize the precinct data and output a table which showed the total votes per precinct.  I can then join this table to the Counties data as a one to one join.

Alternatively, you can join the two data sets using the Spatial Join Tool.  Instead of joining on a common key (I joined on County number), you can join them based on their proximity such as an intersect or contains.

Prop 37 Voter Map created with ArcGISOnce the data is ready to display on the map, you can use “Symbology” of the joined data layer to display a normalized ratio.  Showing absolute numbers of Yes votes does not really tell the whole story as some precincts and counties have greater populations. Normalize the Yes votes by calculating the ratio of Yes votes to total.  This produces the map we were looking for.  Once we add the required metadata, scale, etc, we can export it. (view my map online here)

What did I learn from taking this course?  Spatial analysis is a specialized field which does not differ too much from more traditional data analytics.  The course taught me the special files formats, terminology, and ArcGIS basics.  What is most interesting to me is this map could be made with other platforms like Tableau and PowerBI.  The only difference is the data must be manipulated outside the software (in Excel, maybe) and then visualized.

This brings up a great point.  In traditional analytics and business intelligence, you work with specialized tools which handle a specific part of data.  From the ETL (Talend or Kettle) to analysis (Excel or Python) to visualization (Tableau or Qlik), each segment of the data journey required different software.  Today, the lines are blending a bit.  Solutions like Alteryx combines ETL with analysis, but leaves a lot to be desired in terms of visualization.  Tableau is also able to connect to and blend a variety of data sources, but leaves some to be desired in analysis.

After taking this course I am left with a profound sense of how specialized GIS is. I can understand why it is well worth investing in, especially for geospatial analysis consisting of multiple data layers.  When you consider ArcGIS (or GIS in general) is capable of global level analysis, it takes your breathe away.

My eyes are open to how I can leverage GIS and merge it with my interest in History. Perhaps creating a historic spatial database which illustrates the speed at which Manifest Destiny occurred?  Maybe we can start with a map of Texas and how it was settled over time? Stay tuned…

Thinking Spatial

Thinking Spatial

Spatial analysis has come of ageAs time goes on, our world becomes more and more global.  We also capture more and more data as each day goes by.  Linking the location of this data with time and other attributes, can reveal very profound patterns; patterns at various scales like community to global.

We can answer numerous questions about a lot of different things using GIS software like ArcGIS.  Using the concept of data layers, we can start to analyze data in exponential ways.  We can go beyond statistics on a data table and evaluate changes over geographic space.  We can also use GIS to find the best locations and features with certain characteristics.

For example, Whole Foods uses many different data layers to identify the best locations for their store fronts.  They want the best location which has a population of 200,000 within 20-minutes. They also look for locations with at least 20,000 sq ft, a decent sized parking lot and ease of access along with highly visible (source).

Thinking spatial about some of my own interests, I have come up with two focus areas. The first being related to the “walkabout” I have been on over the past few years.  Where do I want to live as my forever place?  This GIS would take into account numerous data layers such as population, elevation, incomes, education, and access to parks and rivers. Using these data layers, and a few more, I can begin to scientifically hone down where I could settle down.

The second spatial project centers around my love of history.  I am currently reading a book about Red Cloud titled, “The Heart of Everything That Is.”  What piqued my interest was the impact of European Settlers had on the spatial and temporal changes in the new world.  With the arrival of settlers in the east, drove waves of Native Americans west as they fled.  But they fled with muskets, blades and disease.   As the book described this change, I was mesmerized trying to visualize this on a map and in the context of the time.  Throw in some explorers, desperadoes, and outlaws and you have quite a story. But I want to build an interactive story map to illustrate these profound changes.

To think spatial opens the mind, builds the curiosity and becomes a book of its own right. What ways can spatial analysis impact your life? Your curiosity?

 

X-Plane Logbook Stats for 2017

As an aviation geek and armchair pilot, I wanted to have some fun with Tableau Public and my X-Plane Logbooks.   Where have I flown the virtual skies in 2017?  The answer isn’t too shocking, but there are some interesting patterns.  X-Plane Logbook Tableau Data VisualizationCheck out the image below and then head over to the live workbook.

  • 90.7 flight hours with 73% flown in X-Plane 11
  • 57 unique aircraft flown across 178 flights
  • Top aircraft flown include the VSkyLabs Douglas DC-3, Carenado B200 XP11, and FlyJSim 727Adv (version 1 for xp10)
  • Most flights occurred during the day
  • KPAE and KBFI were the most flown airport pairs

Where will 2018 take me?  Not sure.  Perhaps getting out of the western US would be a start.  Maybe even a few international flights are in order.

And, if you need some help with visualizing your data, check out my Tableau page at Spiral Analytics.

 

3 Parts to a Sales Compensation Program

Sales Compensation is not easy.  Throughout my career, I have seen plans which break the sales budget to plans which do are insulting to the rep as they pay too little for a lot of work.  I refer to sales compensation programs as a form of art which requires a bit of science.

3 Parts of Sales Compensation Program

Science is pretty easy as it is understanding how your team should be selling your product and how it translates to the pipeline and corporate goals.  This understanding translates to key performance indicators (KPIs) which one can use to monitor rep performance and team performance.

The art plays in as you develop the actual plan and which KPIs enter that plan.  Average Deal Size, Number of Meetings, or Conference Attendees may not necessarily be the best indicators of sales.  With a mix straight sales revenue compensation (say 2%) and additional kickers and bonuses, the art of using plan structure for influencing rep behavior can take trial and error to get right.

Finally, the best compensation programs leverage transparency, reporting, and recognition. This is plan implementation where making sure the rep understands their KPI progress and how it translates to their paycheck.  Regular reporting and team leaderboard distribution are essential, motivating and drive revenue. A proactive analytics program can ease the calculation and payout of compensation at the end of the quarter.

As a specialist in the field, I encourage you to follow Spiral Analytics, my consulting firm dedicated to sales team optimization and small business promotion.  Follow us on Facebook

 

 

 

Top 5 Best Practices for Rolling Out Sales Rep Scorecards

Sales rep scorecards are that golden unicorn of any sales organization.  The scorecard is a compilation of Key Performance Indicators (KPIs) which are measured against thresholds.  In a rep scorecard, we see a visual interpretation of how a rep is doing for each of the KPIs. An example of which is below:

A Simple Sales Rep Scorecard with three KPIs

Sample Sales Rep Scorecard

Before I dive into best practices, a word on why not a lot of sales organizations have scorecards.  The primary reason is due to organizations struggling with data which best represents the business which makes it difficult for them to setup a KPI, let alone establish effective targets.   An understanding of the analytics continuum is also helpful for understanding the evolution of data practices which need to met prior to rolling out KPIs and Scorecards:

The Analytics Continuum: a blueprint for adoption

Top 5 Best Practices for Sales Rep Scorecards

  • Sales reps, Mangers, VPs, and CROs must all have agreement on the KPI definition, targets, and thresholds.  If one level of the KPI hierarchy is not on the same page as the others, there is very value in using the Scorecard to represent an ideal.
  • Targets and thresholds must be reasonable.  When rolling out KPIs, we often realize that actual performance is far from the corporate ideal. For instance, a Sales Cycle of 45 days is thought to be ideal, but the rep actual is north of 60 days.  Don’t hold this against them, consider rolling out a target of 55 and stepping the target down to 45 days within three quarters of launch.  Be kind to the reps and allow them to catch up.
  • Scorecards must be part of a larger sales communication strategy.  Rolling out a scorecard alone will have an impact on the organization, but the most impressive will happen if scorecards are a part of the larger communication strategy.  For instance, a weekly email can call out wins by reps, it should call out performance, and it needs to call out what needs to be done to hit the goal.  Scorecards are just one piece of the story in sales.
  • Scorecards need to be updated as the business evolves.  Scorecards can never be truly static, recurring reports.  Part of the role of your analytical team is maintain reports as the business changes and evolves.  Scorecards are no different.  From a subtle change of keeping thresholds and targets up to date, to swapping out KPIs for new ones, scorecards are a living animal and requires food to stay alive.
  •  Scorecards are a coaching opportunity, not a punishment tool.  While HR and managers will look at a scorecard and see a rep with all red for their KPIs, this doesn’t mean the rep needs to immediately be put on a performance improvement plan or, worse yet, fired.  Scorecards are coaching tool and enable the manager to work with the sales rep and ask questions like “why do you think your sales cycle is double the average?”  Work with the rep, train the rep, and allow the rep the chance to go for green.

As your team rolls out scorecards across the sales organization, keep these best practices in mind.  Be kind to your reps, get agreement on definition, use scorecards as part of a larger strategy, keep them updated, and use them as a coaching tool.

Need a Sales Team Dashboard?

Monitoring your sales team is a major part of success.  Sales managers and executives need a simplified media to review key performance indicators KPIs to understand how their sales team is performing.

Such a simplified media is a dashboard style report which includes both charts and data tables which report KPIs pertinent to the business.   In a for profit business, typically revenue generation is at the top of the KPI list, followed by product performance, rep performance, and then rep productivity metrics.

Example Sales Team Management Dashboard

Spiral Analytics’ Example Sales Team Management Dashboard – Available for $5 through Fiverr

Since simple is good, Spiral Analytics, the name of my analytics solution company, is offering a gig through Fiverr.  The $5 Gig provides a basic template and setup for a sales team dashboard which follow the metrics above.  Additional charts and the ability to maintain the dashboard for you are available at additional charge.  For more information, send us an email below.

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