By Thornton May
Futurist, Senior Advisor with GP, Executive Director & Dean - IT Leadership Academy

Trend #1: Technology Spending is Bigger and Growing Faster Than Ever Before
The consensus forecast places total global IT spend in 2015 at ~$3.8 trillion. In reality, if you include everything that’s being digitized total global IT spend will~ $20 trillion by 2020. In the years 2000 to 2010 the Compound Average Growth Rate [CAGR] of IT spending ~ -.2%. In marked contrast , CAGR for 2011-2020 is predicted ~ 14+%.

Trend #2: “Shadow IT Will Become “Shallow IT” Will Become R&D
The money being spent outside of IT [i.e., behind IT’s back] is frequently referred to as “Shadow IT.” Historically it was viewed as a bad thing – a reflection that IT was not able to keep up with or deliver fit-for-purpose solutions to the business. Progressive IT shops now view Shadow IT as a demand signal [i.e., the business is holding up their hand and saying this is something I want a technology solution for].

The business is essentially doing pre-enterprise roll out beta testing of possible solution sets. When these experiments surface true user requirements IT can  step in and rapidly commercialize risk adjusted, at-scale enterprise systems.

Trend #3: An Ever-Increasing Percentage of Human Behaviors Will Be Augmented by Technology
By 2020 executives in the developed world will interact will more than 150 sensor-enabled devices daily. Machines interacting with other machines will now do more and more of the routine things humans used to do themselves. For example, by 2020 ~ 30% of new cars will have a self-driving mode.

Trend #4: Organizations are becoming much more empirically driven
High performance organizations will listen to the data and let the data “speak for itself.” It doesn’t matter whether the A/B Test is automated or not. What matters are that the CEO is increasingly saying to the marketing group, “No, it is not up to you to chose which advert we are going to run. We are going to find out which advert we are going to run. We will do that empirically.”

Trend #5: The Scientific Method is Being Embedded in the Software of Our Lives
Increasingly software is being embedded in more and more parts of the business. Increasingly the scientific method is being embedded in this embedded software. In the not so distant future software will tell us what software to use to solve a particular business problem.

Trend #6: We Are On the Cusp of Deeper Systemic Understandings
At a recent MIT symposium Michael Schrage, author of The Innovator's Hypothesis:
How Cheap Experiments Are Worth More than Good Ideas observed that historically in the data space there was a desire on the part of the business to look at a correlation and then declare causality. Schrage was struck at there not being much curiosity and/or investment in more deeply understanding underlying mechanisms – the why of the matter. Imagine that executives who had more time thanks to augmentation were to think deeper about how their business actually operated? We could be on the cusp of a Golden Age of productivity.

Trend #7: Becoming a Digital Company is at the Top of the Enterprise Agenda
51% of Boards of Directors think digital transformation is “critical to implement in the next 12 months.” 27% rate digital transformation as a “matter of survival.”

Trend #8: Somebody has to Lead the Way to Becoming a Digital Business
Marketers are not confident in their digital ability. Line-of-business execs lack familiarity with the technologies of the future. IT leaders carry the baggage of dated legacy systems and everybody hates HR. Who will lead the way to the future?

Trend #9: “Datapreneur” is Entering the Vocabulary
“Datapreneur” a neologism combining “data” and “entrepreneur” is sneaking into the lexicon, showing up in our digital natives describe themselves. A datapreneur is one who makes money with data. Entrepreneurs of all generations have discovered data as one of the shortest and easiest path to influence, wealth and societal impact.

Trend #10: Data Science “Special Forces” Will Be Airlifted in to Value Hot Zones
Creating supra-normal value in the data arena requires a unique blend of not so common skill sets. In the next five years, simultaneous with efforts to develop internal analytic competence and capability organizations will turn to data science “Special Forces” in special instances.