Revisiting Triathlon Intelligence

triathlon intelligenceDuring my triathlon years, I was amazed with the impact data has on a training program.  GPS devices, wearables, and tracking apps seriously changed how triathletes viewed their training.   Rather than going by feel, triathletes could “see” their workouts with data visualizations.  Areas for improvement were quickly identified and brought to the front for full attention.

As technology continues to improve, our wearables get more complex and accurate, and triathlons become more competitive, we need a better way to digest our data. Very much as Tableau has created a better and more robust platform for visualizing and forecasting business data, this same functionality must come triathlon.

What is the real problem?  It is the same problem I tried to address with TrainingMetrix, combining all of a triathlete’s data into a single source to derive insights and forecast future workouts.  To this day, we still deal with separate databases and apps for our workouts and nutrition.  Companies like Garmin and MyFitnessPal have improved integration, bringing nutrition and workout data a tad closer. But, we are still missing the insights… the indicator of diet quality, the indication of over training, and the ability to see progress at the highest level.

This is where my dream of triathlon intelligence comes in.  Combining each data set not just for visualization, but combining the data set in a way which tells the future.  Perhaps I want the crystal ball of triathlon training…  nothing big.  lol

Where does this go from here?  It starts a new era in research and passion.  For myself re-entering triathlon training has renewed my search for the ultimate solution.  In future posts, we will explore some of the solutions on the market including what is good and what is bad.

The Math Every Sales Must Do

As a sales rep you need to deliver closed won deals to meet your quota.  As with all journeys to a goal, there is a hard, rough road and a superhighway, fast and smooth as a baby’s butt.  To earn your commission the most efficient way possible, wouldn’t you want to be on the superhighway? Of course!

The Math Every Sales Rep Must Do

Let me show you how to do some math to start you down your sales superhighway.  The key is to leverage data as much as possible along your journey.  To get started, you’ll need a few data points.  If you don’t have historical trends to use, an estimation is fine.  In fact, you might want to do the math a few times using different number so you understand the impact each variable might have.

Here’s what you need to get started:

  • Monthly, Quarterly, and Annual Quota
  • Average Deal Size
  • Sales Cycle
    • Ideally, Lead Create to Opp Close, but Opp Create to Opp Close can work for expansion reps
  • Win Rate / Close Ratio
    • Both Count of Opps and Value of Opps
  • Lead to Opp Conversion Rate

We will use these metrics and KPIs to calculate a few additional data points.  The first is translate our quota numbers to the number of deals we’ll need to close.  The second is to understand what size pipeline we’ll need to target to hit our number.  Finally, we’ll calculate how many quarters we need to project out and how much pipeline we need.

  1. The Deal Count

The first calculation is quite simple and uses quota and average deal size.  Simply divide the quota for the period by the average deal size and it will tell you how many deals you need to hit your number.  As a best practice, add 1 to the number you get:

(Quota for period / Average Deal Size ) + 1 = number of deals you need to hit your quota

Write these numbers down in a book or journal so you can refer back to them.  You may also want to use an Excel spreadsheet and keep track of the number of deals you need and which accounts will give you those deals.

2. What Size Pipeline Do I Need?

Once we know how many deals we need, we also need to know what size pipeline we need to close those deals.  This is where win rate (also known as Close Ratio) comes in.  You should have two win rate numbers, one based on  COUNT of opportunities and another based on DOLLAR VALUE of opportunities.

Depending on which you want to calculate, use the appropriate set for count of deals and quota.  The math is:

Count of Pipeline Size:  number of deals needed to hit quota +1  / win rate of count

Dollar value of pipeline needed:  quota for period +  Avg Deal Size / win rate of dollar value

Again, write these number down.  This is the size of the pipeline you will need to build to make sure you hit the quota number based on your historical win rate.

3. How Far Do You Plan Ahead?

You may be wondering why we haven’t used Sales Cycle yet.  While we aren’t going to use it in a calculation, we will use to see how far ahead we need to be planning. to hit our number.

Sales cycle can be calculated  a number of ways so be careful and understand what the number you have means.  For instance, many clients I have worked with in the past have used a sales cycle which measures Opportunity close age, i.e. Opp Close Date minus Opp Create Date. This is misleading if your business includes prospecting.  A true sales cycle uses either Lead/Contact create date or Account First Activity Date.    Make sure the number you are using a sales cycle which represents the true time frame you need to work your leads/contacts and close your opportunities.

quota period in days / sales cycle in days

If your sales cycle is 45 days, planning one quarter ahead is sufficient.  But if your sales cycle is 105 days, you must plan two quarters ahead.

It’s a Wrap

With these three pieces of math in mind, you are well on your to establishing the foundation for your superhighway to 100%.  Understanding what it takes to hit your quota number, how long and planning far enough ahead is huge and gives you a head start against your peers.  You may be amazed at how many reps don’t DO THE MATH.

 

Understanding Our Past: Support LIDAR Mapping at El Pilar

In the late 1990’s and early 2000’s, while I was attending University of California, Santa Barbara, I had the honor of working with Dr. Anabel Ford and her resilient crew on various projects surrounding the Maya site of El Pilar.   From archaeological excavation to mapping, to cutting trails, analyzing artifacts, and building predictive models, the time I spent on this project was phenomenal.

Recently posted on my Facebook page was a notification the Dr. Ford is undertaking a new project, mapping El Pilar with LIDAR to better understand Maya settlements beneath the thick rain forest canopy.  Please follow this link for more details.

Support the El Pilar LIDAR Mapping Project

They are currently seeking $2,700 in funding via Experiment.com, a crowdfunding platform for scientific research.  $2,700 is a bargain for the wealth of data and insight this team of researchers will acquire.  At 30% funded with 22 days left, let’s push it to 100% and beyond!

Cheers!

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.

An Example of the Quantified Self: Steps

Wearable trackers are all the latest rage!  From a FitBit to a Microsoft Band to old school pedometers, the latest health craze is about steps.   Whether you joined the office fitness challenge or just want to get moving a bit more, the concept of tracking steps is the most popular metric of the quantified self in 2015.   What a perfect metric to start a series of posts showing examples of the quantified self.  The objective is to show the wide variety of metrics an individual can use to make their life healthier, more productive, and happier.

Tracking Activity: Steps

The graphic below is my steps history as recorded using an app called Argus on my iPhone 5S.  The app is simple, turn it on, and it does the rest.  It records steps as you move through the motion sensor.  Of course, the drawback is, it only records steps if the phone is with you and on your body.  For example, if I was on an elliptical, the phone would have to be in my pocket to record the steps, placing it on the machine doesn’t work.

Creating a Custom Quantified Data Visualization

To create the dashboard below, I entered my step data into a Microsoft Excel spreadsheet, added a few formulas for day of week and location and picked a data visualization platform. While I could have created a few charts from a pivot table in Excel, I decided to give Qlik Sense a test drive.  Qlik Sense is a lighter, consumer oriented version of the powerful Qlikview data discovery and reporting platform.  Qlik Sense is easy to use, just select your data source (Excel in my case), select your dimensions and measures and you are off to the races.

quantified self data visualization

Using Qlik Sense to visualize steps data from Argus

Raw Data: Steps by Day

The top graph shows raw steps by calendar date.  While there isn’t too much to see here at first glance, you can see clear dips in the pattern which maybe the weekend.  You can also see the data at the right tend to be a slightly higher than the data to the left side.

Steps by Day of Week

By adding a dimension called “DayName”, we can average steps by day of week.  In the orange chart to the right, the most active day is Monday, followed by Thursday and Sunday.  The lowest is Wednesday.  Fitness improvements come with consistency.  Being the difference between highest and lowest is fairly great, we can focus on being more active on Wednesday’s.  Tracking the change over time will help us be more consistent with our activity.

Steps by Geography

I also added a dimension called “location” by tagging each day with where I was.  I often split time between Washington state and Santa Barbara with days in between flying. The green chart to the left shows a pretty interesting pattern, I am far more active when in Washington state compared to Santa Barbara, This is probably due to the recreational abundance in Washington, such as the hiking trails around Mt. Baker and the walking we do while downtown.  Santa Barbara is also a much more isolated location by comparison.  Perhaps, if I want to be more active, I should stay in Washington state.

The Fundamental, Visual Flaw

You might be asking, what flaw is there is there in the above dashboard?  It is hard to see because it is not there. One of the best CEO’s I ever had the honor of working for said, “if it is important enough to put on a chart, you better damn well have a goal indicator with it.”  I agree.

Throughout this post, I mentioned goals such as covering 10,000 steps in a day, and increasing Wednesday activity.  The charts above should include an indication of these numbers.  The charts are essentially naked without the indicators and the user viewing them loses the context of the rest of the data.

Always include a goal indicator when creating data visuals, the context is essential.

Conclusion

This is one example of using data visualization to improve personal life.  Activity is one of the primary factors in achieving and maintaining good health.  Using a fitness tracker and visualization tool like Qlik Sense can be effective.  Just understand the privacy policy and how the wearable tech company may use your private data.

Triathlon Intelligence: A Calendar View Template For Triathletes

For the past few years, I have been not only training for triathlon, but also talking to fellow triathletes about triathlon performance.  The concept of triathlon intelligence is alive and well in the minds of anyone looking to improve their triathlon finish times.  Not finding much excitement with the training and workout logs on the market, I created TrainingMetrix  (out of business – Oct-2015)to explore the intersection between data and triathlon, as well as data and fitness in general. From usability and access to data to creating KPIs for workouts and nutrition, TrainingMetrix took an open exploration of this often overlooked intersection.

Our latest template, based on feedback from our users, is a modification of our free Triathlon Foundation Template and adds the ability to view both workouts and training plan in a calendar view.  Now, you can see your workouts compared against your plan! This is in addition to the powerful performance dashboard already a part of the free template.  The new Calendar View Template also allows you to build your own training plan.

calendar view triathlon workout and training log

Track progess, merge your plan and workouts into a calendar view, and create/modify your own training plan, the Calendar View Template is a powerful for triathletes

I am excited to show off this latest template.  We are combining a number of KPIs for triathletes into an easy to use template which resides locally on your computer, so your data is private and protected.  Being based in Excel, the template provides a foundation for you to customize and create your own charts and data views.  The power of workout progress and trends come alive.  The ability to create and modify your training plan is another powerful tool.  Lastly, the comparison of training plan to actual workouts is the intelligence the triathlete needs to stay on track, plan ahead and adjust as necessary.  For more information, please visit the Calendar View Template website.

What’s next for TrainingMetrix and I?  A lot, stay tuned, we are just getting started with understanding this intersection, data and triathlon.

Update 10/15 – TrainingMetrix was shut down in October 2015 due to increasing costs and lack of an effective business model.

Anti-Cloud Based Tools for Personal Intelligence

Creating a personal intelligence platform for self tracking has never been easier.  While technology continues to push us toward the “cloud” and SaaS as a strategy of revenue generation, we cannot overlook the tried and true platforms available to keep data on your computer and away from prying eyes of Analysts.

As a data visualization and KPI development guru, I love finding those interesting trends in my own life that drive smarter, better habits.  If you are like me, you don’t feel comfortable sharing your dirty underwear with Mark Zuckerberg and you really wonder what Google is doing with all of that data they keep acquiring.   By maintaining a self database on my desktop computer which I can add to and tweak at a whim, I am able to give myself peace of mind and control over MY data.  Curious, about what KPI’s I track?  Stay tuned, that is a topic of another post.

Without further ado, here are some tools that you can use to create your own personal intelligence platform on your local computer:

  • Microsoft Excel
    • A stunningly powerful tool to use for even the novice user.  Create your own tables, link them how you want and design your own graphs and dashboards at your own pace and complexity.  Available for both Windows and Mac.
  • Numbers
    • A Mac only platform designed to compete directly Microsoft Excel which offers much the same functionality, but lacks some advanced capability compared with Excel.  The simplicity and robust visual que are 2nd to none, but as the data set grows, you may be wishing you chose Excel in the beginning.
  • Qlikview Free
    • I have been a fan of Qlikview for years.  I love the ability to create charts and dashboards from Excel spreadsheets and the gnarly level of interactivity that it provides.  The learning curve isn’t as steep as one might think and well worth a few minutes reading their documentation.   The limitation here is the limited number of shared files you can open.  Windows only.
  • MySQL / Apache / PHP / HTML5 / HighCharts
    • Ok, if you are going with this option, you are a true geek with coding ability.  This isn’t for the lighthearted as configuring MySQL, Apache, etc etc will take time.  But the advantage is you are left with an enterprise class database and a truly blank slate in regards to dashboards.  You can even create your own forms in HTML to add data.  Mac/Linux/Windows
  • Microsoft Access
    • If you need something in between Excel and MySQL to store data, Access is a great option and can interface with Excel graphs and dashboards.  With a mild learning curve, the ability to store any kind of data, and the convenience of a query builder UI, Access makes for a very robust solution. But, it lacks more advanced visualization, so be prepared to connect Excel to Access. Windows only and available with Office Professional.

As you can see, creating a Personal Intelligence platform off the cloud is possible.  You can take full control of your data and keep it private at the same time.  As data becomes more and more of a commodity and SaaS business models continue to nickel and dime everything, home based data management will be more and more appealing.  Excel is the perfect anti-cloud.