Exprodat is focused on helping our clients in the petroleum sector make better use of Geographic Information System (GIS) technology and we are sector leading specialists in the use and application of ArcGIS technology from ESRI to E&P spatial challenges.
Every organisation that takes on board GIS wrestles with the question: how much training do we need to purchase? Because one of our three core services is GIS training, we get asked this question a lot, maybe not directly, but when organisations talk to us about what we have to offer, this is always an underlying question. So, is there a training metric you can calculate that will tell you how much training each of your geoscientists needs in order to be an effective user of GIS tools?
I’d like to propose using a metric that we’ll call the ‘Training Gain’ as a potential solution to help decide how much training you need, while not actually suggesting that this single metric will be the answer to all questions. I think of Training Gain as representing the total increase in productivity and effectiveness that training might make to an individual’s performance, versus their likely performance if they were just left to learn-“on-the-job”.
We have created a very simple model to help visualise the impact that training can have on a member of staff.
For technical boffins, the equation is:
SLTM = SLLM + ((1-SLLM)*(MSG + (NTE * SGE)))
SLTM = skill level this month
SLLM = skill level last month
MSG = monthly skill gain from on-the-job-osmosis
NTE = number of training events last month
SGE = skill gain from one training event
I suggest graphing the level of technical GIS skill of an individual geoscientist over 36 months (it could be any length of time, but let’s keep it simple) as three years is a useful period of time in terms of learning new skills.
The following assumptions apply to the model:
- The level of technical skill in GIS is essentially finite, so the model imposes a scale on GIS expertise of 0-1, where 0 skill represents a geoscience professional with no GIS expertise and 1 represents a professional with an expert skill level.
- Rarely would we expect a geoscientist using ArcGIS to become a GIS expert, but with training and experience, in 3-5 years, it may be possible for geoscience professionals to get close to expert level if they were so inclined and had an aptitude for GIS.
- Professional geoscientists acquire ArcGIS software skills on-the-job through self study and through transfer from colleagues, even without training. This is a continuous process, but in busy organisations this might also be a very slow process.
- Training events provide a second method of learning and we believe that the impact of training events is in being concentrated and focussed skills acquisition from GIS experts.
Experience at Start: how much ArcGIS skill did the staff member have at the beginning of the modelling period, on a scale of 0-1. If they have never even heard of ArcGIS then assign a 0. If they are familiar with the concepts and ideas, but have done nothing more than look over someone’s shoulder, give them a starting point of 0.05 (perhaps still too generous!). Maybe they’ve used ArcGIS to open up someone else’s map and have a look? Then score 0.1. Like all modelling use your best judgement, this is subjective, and the goal is to gain a better feel for what training gives you over a period of time.
Skill gained through on-the-job experience: a steady monthly gain in skill from using and working with others who are using ArcGIS. If we posited that you could acquire an expert skill level in three years (36 months) of simply using ArcGIS on a frequent basis that would mean an annual skill gain of > 80% on top of what you already know. For all but a few exceptional individuals that is far too high, perhaps 12% each year or 1% each month is a more realistic value. Again, play with the numbers, what seems right to you?
Skill gained through Training Event(s): the skills gained from a single training event is a discrete nugget of professional development aimed solely at raising an individual’s skill level. This parameter represents the amount of skill gained as a proportion of what you already know. It is subject to the law of diminishing returns! In other words, you can only ever learn a proportion of what is known as you increase in skill level, additionally learning (although perhaps critical) will only bring smaller increments of knowledge.
Training Events: this parameter allows the user to set the timing and number of training events that an individual undertakes during the period being modelled.
To Be Continued…
Please feel free to download the model (Excel file) and have a play.
In Part II of “How big is your training gain?”, I’ll provide a couple scenarios that I’ve run, but if this is an area of interest to you – you should have a play with this very simple model first, without me biasing you any further!
Posted by Chris Skelly, Training Manager, Exprodat.