Ensuring your workforce adapts and changes in an Exponential Society is crucial. Leaders need to allow employees to receive appropriate training and feel empowered to grow and adapt as their career, their industry and technology demands.
It’s top of mind for many of our clients. And if it isn’t on yours, it should be.
My own career path is an example of how skills adapt, grow, evolve and sometimes resurface throughout a career.
Over 12 years ago now, I earned a master’s degree in Geographical Information Systems (mapping systems to most of us). At the time, I didn’t think much of it. What I knew was that I loved the experience, loved the modules and loved working around the clock whenever I wanted to go into the Computer Labs at University.
What I didn’t realise was that mapping was the foundation of something bigger and would become an exponential technology through Google Maps.
As part of the course, we did weighted regression analysis, neural networks, automation of code, Web services, Black Box algorithms and some amazing analysis of data in order to predict the best place to locate things, such as highways, environmental protection areas, fire and flood risks. Today this would be known as Data Analysis.
Most of this, I had forgotten or moved to a less prominent place in my brain as I gained and used other skills. But it popped back into view one day in April when I was sat in a workshop at the CSC TechCom conference.
The workshop, “Big Data – Deep Dive,” described examples of where we have successfully helped clients on the big data transformational journey. Jerry Overton, one of our data scientists, showed us his developmental working environment. What shocked me was that I understood it all from my university days. It had been renamed big data, but what Jerry was showing was regression analysis and coding, and I understood.
Those of us who did map-making in the late 1990s built the codes to get maps to run together and process data streams, similar to Machine Learning. We also had to do much creating and cleaning of the data before it was ready to be used. Sometimes we even had to work with SMEs to collect data and understand the knowledge associated with it.
We were used to dealing with data from numerous sources, internal and external; different types of data, static and dynamic, realtime and current, Raster and Vector, networked and non-networked, 4D, 3D and 2D data, structured and unstructured. We were used to metadata. We understood how to process and place aerial photography into a map.
We knew how to firstly code in avenue, then in VB, then in other languages as needed. We knew how to integrate with the latest super database from SAP or Oracle Open and Closed sources. We knew what it meant to have relational databases. We understood how to map GPS coordinates onto other datasets and stream live data from Tilt stations in the field which were run remotely by solar power. We were used to change-only updates and seeing our environment change at an exponential rate.
When the Google transformation occurred, over night we knew that data was no longer special. Everyone now could access mapping data. This was good for everyone, but not necessarily good for the industry at the time.
Many companies had to reinvent and partner in order to survive. The spatial industry was turned on its head, and it had to become a corporate entity where anyone could access whenever they wanted. The spatial industry was reinvented.
Geospatial experts were used to being overloaded with information back in the 1990s, in a world where data was everything for us. Without data, we could not do our jobs. This is true today.
“Data is the new electricity” said the CEO of Microsoft in 2016. Data is and still will be a commodity, without which we can not understand problems and suggest solutions. For us, data is the key to understanding the reasons why and to making important but wise decisions.
A colleague of mine recently said, “Sarah you are an optimist, but an optimist who bases her thoughts on facts.” My response is that I am a data scientist, one with a background in map- making and thinking about helping the clients answer complex questions first.
So the purpose of this blog is to remind all of us to be ready to change and to encourage leaders to empower those with deep knowledge in one area not to be scared to branch out, explore something new and innovative. Learn a new technology or perhaps try a different market.
Have a go at artificial intelligence, machine learning, robotics, blockchain, optimisation, virtual reality, augmented reality, analytics, big data — and don’t stop learning. Think about how your own area of expertise can be used in conjunction with other newer technologies.
Learning new skills and teaching others in your organisation to improve and grow is crucial to future proofing your success — and your clients’. Think about how you can help them to see their business through futuristic eyes. Using and showing new technologies and ways of doing things might be a start.