Advanced guide to Game Plan
If you want to edit an Analysis page, make your way to that page and then click on the “Edit Panels” pencil icon in the top-right of the Analysis page window. This will put the page into editing mode, you’ll see the grid outlines and you’ll be able to click-and-drag to rearrange the Panels on the page. In editing mode you can:
Delete, move and duplicate panels - By clicking on the “ …” at the top-right of any panel and selecting either “Duplicate” to create a new, identical panel on the same page, “Copy to…” to create a new, identical panel on a different page, or “Delete” to remove the panel from the page.
Create new Panels - By clicking on the “ + “ button that appears in place of the Edit Panels icons, this will open the Panel creation window, where you can choose new panels to add. These include blue Directus-built panels, Bar charts, line charts, lists and metric lists, or you can add in filters like Global variables and Global relational variables (more on filters is located below).
Black labelled Panels were created by Power Trip and include a more advanced bar chart (the Column chart), a stacked column chart, and a ratio meter.
DIY Dashboards and analysis
Editing and creating Analysis pages
There are two ways to create a new analysis page, either copy an existing page or create a new one from scratch. It is always faster and easier to copy an existing page that is similar to the one you want to create. You won’t need to add filters, the formatting will remain consistent and it will be located next to the original page in the left-hand menu. All you will need to do is change the charts and language on the new page.
To create, copy or edit Analysis pages, head to the Analysis contents page via the line-chart icon on the left-most menu bar. You should see all of the existing Analysis pages lined up in the same style that the Content section displays data.
Click on the blue “ + “ icon located in the top-right of the window to create a new page, or click on the three vertical dots to the right of the Analysis page you want to copy and select “Duplicate Dashboard”. If you want to edit the description, title or menu location of an existing Analysis page, click “Edit Dashboard” instead.
Controlling where it appears
Creating a new Analysis page, or editing an existing one, allows you to change where and how the page appears in the list. Game Plan ranks each page alphabetically, based on its Name. However you can change this by Sorting and Grouping pages together.
Sort - Adding a number here will interrupt the Alphabetical sorting. Dashboards with a number will be listed first, and in ascending order (1 will be listed at the top, 2 second, 3 third etc.).
Group - Adding a grouping code to your page will determine how it appears in the menu on the left-hand side of the Analysis tab. Pages with the same grouping code will appear in the same nested menu. A grouping code is a number, followed by a full stop, followed by the nested categories separated with a “ > “. The number tells Game Plan how to rank the top-level group and the nested categories while the “ > “ tells Game Plan where to place the Analysis page in the menu system.
For example, the grouping code “3. Utilisation > Fleet-wide” will mean anyone looking for your Analysis page will find it under the top-level “Utilisation” category, then in the second-level “Fleet-wide” sub-category on the left-hand menu. the Utilisation category will appear 3rd from the top.
Editing and creating Analysis widgets
Each Analysis page is essentially a grid with different data visualisation widgets (called Panels) arranged across it. Building or editing an Analysis page simply requires adding, removing, rearranging or changing these widgets.
Selecting the Panel you want to add will then reveal the details you need to add to make your chart, filter or metric functional by linking it to the data in Game Plan.
Creating a Panel and selecting data categories
When you create a new panel that displays information (for example, a bar chart of a metric list) you need to tell the panel which information you want it to show and how you want that information to be filtered.
First, create a new panel, then add settings from top to bottom changing the following:
Collection - This is the ‘Collection’ of processed data that you want to visualise. There are 5 main, useful Collections you may want to use when creating your Panel, they are:
Car Record - This collection holds information about the vehicles in your fleet, like make / model and registration.
Daily Data - This collection holds all of the EV simulation results. *important* If you are using the Daily Data category always remember to add “Model > ID” as a filter. Power Trip runs the same simulation for different Models of EV, if you don’t filter for Model ID then your Panel will display information from multiple simulations all at once.
Time bucket - This collection holds the daily, hour-by-hour breakdown of where/how each vehicle in your fleet spends its time.
Trip Records - This collection holds daily utilisation information about each vehicle’s travel. Including distance, routes, fuel use, emissions estimates and parking locations.
Trip Calculations - This collection holds any custom utilisation information, by default this is information about commute estimates, such as work vs commute travel distance and time.
X Axis / Aggregation / Field / Value - These refer to the specific data field / type within the Collection, for example the DistanceKM field within the Trip Records collection will provide you with the total distance travelled each day by vehicles in your fleet, in km. While the Distance field in the same Collection will provide you with the same distance, but in meters. Useful fields in each collection are:
Car Record
Car Records contain information about the real vehicles in your fleet.
Active - True or False depending on if the vehicle’s telematics provider is currently sending Power Trip data.
Rego - The registration number (License plate) of the vehicle.
Make, Model, Variant, Sub Model, Vehicle type - Specific manufacturer details about the vehicle.
Fuel type - Whether the vehicle runs on petrol, diesel, hydrogen, electricity or some combination.
Fuel economy - The litres consumed by the vehicle for every 100km travelled.
Engine size - The engine size (in ml) of the petrol/diesel/hybrid vehicle.
CO2 - The rated grams per km of CO2 emissions assigned to the vehicle by the NZ Government.
Groups - A list of any groups this vehicle is a part of within Game Plan.
SoH, SoC, Driver, Latitude, Longitude, Speed, Ignition On, - The last, live data points recorded from your provider.
Daily Data
Daily Data records contain EV simulations that Power Trip has run across your fleet. Each record represents one 24h period of driving for one vehicle (Car Record) in your fleet, based on any telematics data it recorded on that day. You can run multiple simulations for the same Car Record so it is essential that you include Model in any filters you use when creating reports or charts based on Daily Data. Failure to include Model will mean all simulations for the different EV makes and models you’ve selected are included in your report or chart, not just one. This will inflate any energy or battery % numbers several times over.
Model - The EV model that was used to run this simulation. ALWAYS include Model > ID in your filters if you are analysing the Daily Data collection, otherwise you will be analysing multiple simulations at once.
Energy - The simulated number of kWh Power Trip calculated for this vehicle + EV pair for any 24h period of travel.
Additional Energy - The estimated kWh a vehicle might need to spend public charging for any 24h period of travel. This is calculated as Energy (described above) minus the usable battery capacity of the simulated EV model (i.e. simulating the top-ups required by an EV that starts its day on a full charge).
Date - The 24h period of travel that has been simulated.
Longest Leap - The kWh required to travel between the two charging stations that were furthest apart along this vehicle’s journey, this is used to estimate the feasibility of routes done by the vehicle.
Percentage - The energy required to cover that vehicle’s driving on one day, converted into a percentage of the simulated EV’s accessible battery capacity (e.g. 40 kWh of travel is 68% of the Nissan Leaf e+ 59 kWh battery)
Percentage Range - The battery capacity required, rounded up to the nearest 10% for the purposes of showing how many days a vehicle would have used similar battery capacities (e.g. 20 days would have needed 0% to 10%, 30 would have needed 10% to 20%)
Num DC Chargers - The number of DC fast chargers positioned along the route your vehicle travelled.
Num AC Chargers - The number of AC slow chargers positioned along the route your vehicle travelled.
Longest Leap Percentage - The largest amount of energy (in terms of % of your chosen EV’s usable battery capacity) that would have been required to travel between the two charging stations with the longest distance between them where no other charger is available. If Longest Leap Percentage is greater than 100% then chances are your chosen EV would not have been suitable for a route your current car travelled on that day.
Distance - The estimated distance covered by your vehicle on one day, measured as a straight line in between each data point your vehicle’s telematics provider generated as it was driven.
Distance EVNav - The estimated distance covered by your vehicle on one day, measured by planning a route along the roads your vehicle travelled on and obtaining the distance from the map. This is slightly more accurate than the previous method, but more prone to failure if there isn’t enough data.
Num Stops - The estimated number of charging stops your vehicle would have had to make on one day if it had been your chosen make/model of electric vehicle.
Time Bucket
The Time Bucket analysis breaks each day of driving down into 24 hourly buckets of time. Each hour or “bucket” contains a % breakdown of the general way your vehicle spent its time. For example, a vehicle that was parked at the office at 3:00pm, travelled from the office to a client from 3:20pm to 3:40pm and was then parked at the client from 3:40pm to 4:00pm would have spent 33% of the 3pm time bucket at the office, 33% driving and 33% parked elsewhere.
Date - The day that the Time Bucket occurred on.
Hour - The beginning of the hour that the Time Bucket represents. For example, hour “2” captures what your vehicle did between 2am and 3am on that Date.
Idling - The percentage of time the vehicle spent idling in this bucket of time.
Unknown - The percentage of time our analysis couldn't account for (e.g. due to an error with the telematics device)
Home - The percentage of time the vehicle spent parked at home in this bucket of time. Home is assumed to be the location of the vehicle at 2am each day.
Office - The percentage of time the vehicle spent parked at one of your designated offices in this bucket of time.
Driving - The percentage of time the vehicle spent driving in this bucket of time.
Elsewhere - The percentage of time the vehicle spent parked anywhere that wasn’t designated as ‘home’ or an office location in this bucket of time.
Trip Records
Trip Records are collections of telematics data that summarise all of the driving your vehicle (Car Record) has done within a 24 hour period.
Day - The 24 hour period that the trip record pertains to.
Distance - The distance travelled by your vehicle on this day, in meters
Distance Km - The distance travelled by your vehicle on this day, in kilometers.
Fuel Idling -The estimated fuel used by your vehicle on this day while the vehicle was switched on, but not moving, in litres. This is based on the vehicle’s engine capacity and fuel type.
Total Fuel used - The estimated fuel used by your vehicle while driving and idling on this day, in litres
IgnitionOn - Separate Trip Records are created for IgnitionOn (where the vehicle drove) and IgnitionOff (where the vehicle parked).
Polyline - The polyline is an encoded route that contains information about the route taken by the vehicle on this day (if ignitionOn = True) or the stops the vehicle made along the way (if ignitionOn = False).
Fuel Costs - The estimated fuel used by your vehicle while driving on this day, in litres. (This field is called “Fuel Costs” because it was previously a dollar estimate, however it was recently converted to litres to allow for variable fuel prices in Game Plan).
Fuel Savings - The estimated fuel avoided by your vehicle while driving on this day (applies to electric vehicles only). in litres.
Trip Calculations
Customised analyses are stored in Trip Calculations. Currently these are limited to commute calculations, but others are on the way.
Date - The day (24 hour period) for which the trip calculations have been done.
Distance True - The total distance travelled, in km
Distance Commute - Game Plan estimates commute distance whenever a vehicle travels from “home” (defined by wherever the vehicle was parked at 2am on that day) and a designated office, or back.
Distance Work - The total distance travelled for work. This is travel that did not start/end at an office and home. Where a commute is detected, if additional stops are made along the way, the commute distance is calculated as the direct, shortest route to the office from “home” (or return) and the rest of the actual distance travelled is added to “work” travel. This assumes that stops made on the commute, and the deviation in travel, are work-related.
Time Commute - The time spent driving along routes detected as commutes on that day.
Time Work - The time spent driving along routes that were not detected as commutes on that day.
Num Direct Commutes - The number of detected commutes (where a vehicle started the trip at a designated office or at the location detected as “home” for that day, and ended at either an office or “Home”) during that 24 hour period.
Num Indirect Commutes - The number of detected commutes where a vehicle also made additional stops along the commute during that 24 hour period.
Num Commutes - The total number of commutes detected during that 24 hour period, direct and indirect.
Is Weekday - True if the date is a weekday, False if the date is a workday.
Setting a Panel’s function
When you create a panel (e.g. a chart, table or list on an Analysis page) you need to tell the panel what it needs to do with the data it’s displaying. This is called the “function” and the types of functions available are:
Count - The panel will count the number of data points that meet your filters, regardless of the type of data you’re accessing. For example, you can count the number of vehicles that were used to drive more than 100km over a 3 month period.
Count Distinct - This is similar to Count, except it will only count unique data points and will ignore duplicates. Using the example above, Count Distinct will tell you the number of cars used to do over 100km of driving at least once in the 3 month period, while Count will tell you the number of times any car was used to drive more than 100km.
If your fleet had 2 cars and one of them drove 101km twice and the other only drove less than 100km, then Count will return 2 and Count Distinct will return 1.Average - This returns the sum of the values of the data you’re accessing, divided by the count of the values to give you the mathematical average.
Average Distinct - As with Count Distinct, Average Distinct will calculate the average, but using unique data values only and removing any duplicates. This can be useful when reporting on unique data points like car registrations, but avoid using it when reporting on data like Distance, as it will ignore any days with the same distance travelled as other days, which will end up skewing your report.
Sum - Sum adds together the values in all of the data you are accessing in your panel. If you are accessing Daily Data remember to include Model in any filters you set, otherwise you will be adding data from multiple simulations!
Sum Distinct - Sum Distinct adds values that are unique and ignores data points that are identical, For example, if two different vehicles drove 100km on different days and you are using the Sum Distinct function across their Distance, then only one of these two data points would be used in the Panel due to the distance travelled being identical.
Min - Searches the data points on your panel for the smallest value in the data you are using.
Max - Searches the data points on your panel for the largest value in the data you are using.
Creating a filter
Filters are essential parts of panels. Without a filter your panel either won’t work, or it will try to display all of the data in the collection you’ve chosen to use on the panel. Displaying too much data on a panel can slow the operation of your Game Plan dashboard down.
Filters can be used on any field in a collection, not just the data that is displayed on the panel and you can add multiple filters to a panel to closely refine what your panel is showing.
When creating a filter, you first need to choose the data field that the filter is working to restrict, and then you need to tell it how to restrict that field. Filters in Game Plan offer the following functions:
AND - Group any of the filters below together, only data that meets ALL of the criteria grouped under an AND filter will be selected. E.g. Vehicle registration equals ABC123 AND distance driven is greater than 100km. Note, AND is the default way that top-level filters operate.
OR - Group any of the filters below together, only data that meets ONE of the criteria grouped under an OR filter will be selected. E.g. Vehicle registration equals ABC123 OR XYZ456 will select all vehicle records that are equal to either of those registrations.
Equals - Select only data that is equal to your input (can be numbers, text or otherwise. Note, this is case sensitive).
Doesn’t equal - Select only data that is not equal to your input (can be numbers, text or otherwise. Also case sensitive).
Less than - Select only numbers with values smaller than your input.
Less then or equal to - Select only numbers with values the same as, or smaller than your input.
Greater than - Select only numbers with values larger than your input.
Greater than or equal to - Select only numbers with values the same as, or larger than your input.
Is between - Select only numbers with values that are in between the smaller and larger of two inputs you choose.
Isn’t between - Select only numbers with values that are not in between the smaller and larger of two inputs you choose.
Is null - Select only numbers that equal zero,
Isn’t null - Select only numbers that are not equal to zero,
Is one of - Select only values (text, numbers or otherwise) that are in a list of inputs you specify. Note, if you want to use global variables for ‘Is one of’ filters you will need to delete the “[“ and “]” brackets from this filter before it can be used.
Is not one of - Select only values (text, numbers or otherwise) that are not in a list of inputs you specify.
Creating Panels that control other panels (Global variables)
To create a flexible, responsive dashboard you need to be able to change variables (vehicle registration, date, minimum distance etc.) on the fly without having to click through, panel-by-panel, to edit the filters. This is what Global Variables are for and there are two types:
Global Relational Variables are panels that you can assign a data collection to and choose one or more data point from that collection. This data point can then be used in a filter.
Global Variables are panels that you can add a number or text to, that will then be passed through into the filters on other panels. For example, setting a variable distance as the minimum distance in other panels.
Setting a Global Relational Variable (above)
Add a new panel and choose the “Global Relational Variable” option.
Enter a name for this variable under “Variable Key”. This is what you will use when you set up filters in other panels. The Variable Key must be unique otherwise it will interfere with any other variables you have set up with the same key.
Choose the Collection that the Global Relational Variable will use (e.g. Car Record to filter only for specific cars, Daily Data to filter for EV Simulation specific variables like Model or Date, Trip Records to filter for utilisation variables)
Use the + button to add a Display Template. This is what the person using your panel to choose a variable will see, for example choosing Car > Rego will display the registration number, while choosing Car > ID will display the Power Trip ID which a user is less likely to understand.
All other fields are optional, but filling them out will help another person better understand what your Global Relational Variable is doing and why you’ve set it up.
Click on the Tick button at the top-right of the screen to save your choices and add the panel to your Analysis page.
Setting a Global Variable (above)
Add a new panel and choose the “Global Variable” option.
Enter a name for this variable under “Variable Key”. This is what you will use when you set up filters in other panels. The Variable Key must be unique otherwise it will interfere with any other variables you have set up with the same key.
Choose the type of variable you want the user to select, a number (integer, decimal, float) or text (String, text) or a True/False indicator (binary). The variable the user chooses needs to align with the type data you intend to filter for (e.g. Rego is a String, Distance is an Integer).
Set a default value, this is what the filter will automatically be set to when the user opens your Analysis page.
Choose the Interface, this is the type of display the user will use to set your variable.
Every other option is optional, but filling them in will help other people using your Global Variable panel understand what they need to use it for.
Click on the Tick button at the top-right of the screen to save your choices and add the Global Variable selection panel to your Analysis page.
Linking a Variable to a Filter
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Tips, tricks and things to keep in mind
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How we structure your processed telematics data
Accessing your data
Your data is stored in as ‘Collections’ across a series of different Data Models. Most Data Models have been hidden from view to prevent anyone from accidentally deleting or changing anything.
You can access your data by heading to your Game Plan settings, finding the Data Model you want to view and then clicking on the ‘…’ on its panel and selecting either “View Content” to look at the data yourself, or “Make Collection Visible”. Do not click “Delete Collection”!
Data collections / Data Models
Each Collection or Data Model is basically a table of data, similar to an excel spreadsheet. Every entry in a collection represents a row of data, similar to a row in a spreadsheet.
For example, the EV Models Collection holds information about the different makes/models of electric vehicle that are used in the simulations run across your telematics data. Clicking on one of these records will allow you to edit the details about that EV (e.g. by adding additional weight or battery capacity).
The information below describes how each of the main utilisation and EV simulation Collections are structured and what you need to keep in mind when you’re using each one.
Trip Records - Utilisation based on distance travelled and fuel used
Game Plan groups your telematics together into 24h blocks, from midnight one day to midnight the next. Trip records are
Trip Calculations - Utilisation based on commuting and custom scoring
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Time Buckets - Utilisation based on time in use
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Daily Data - EV feasibility assessments
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Car Records
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EV Models
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Downloading data
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