Data science is an interdisciplinary field. It pulls together theories, processes and people knowledgeable about statistics, mathematics, physics, information science, engineering, machine learning, you name it.
In case you have been hiding under a rock since 2011, the industrial Internet of Things (IoT) is flexing its muscles full-force on how we do business, how our businesses are modeled, how we make decisions and how we communicate with each other.
Pertaining to the “how we make decisions” part of that last sentence, the days of anecdotal decision making are long gone, my friends. “I think” or “I recall” simply do not cut it any more.
There is an app for that, there is an algorithm and somewhere there is a data lake just waiting to be distilled down into a data swimming pool, data bathtub, data bucket, data cup and bite-size data thimble.
Data scientists, big data and predictive analyses rapidly are becoming the fulcrum against which your business growth, expansion and sustainability are leveraged.
Got a data scientist lurking around your own organization? How about your software vendor’s organization?
Regardless of the size of your business, continuing to ignore the importance of collecting and analyzing data to make data- and insight-driven decisions makes you non-competitive in the industrial IoT business ecosystem.
Data scientists are the new “Them.”
Since 2009, I have been writing about the importance of multidisciplinary, cross-functional collaboration in creating line of business value for your and your clients’ organizations. I coaxed and cajoled you to at least have a cup of coffee with one of Them: the engineering, finance, IT folks within your organization.
You know Them. They are the folks that business people marginalize from customer-facing business development conversations. Why? No one on the business side of the table truly understands what the “geeks, nerds, techies” are saying to them.
Know any of “Them” in your own organization? “They” are intimidating, aren’t they? “They” make you feel inadequate, uninformed, even stupid. Well, isn’t it time to “unstupid” yourselves and confront what intimidates you?
I don’t know about you. However, I’ve made a career out of collaborating with wicked smart people who initially intimidated the heck out of me. I just was never afraid to ask what I thought were stupid, curious, inquisitive questions. When you ask questions that scare you, you create collaborative conversations which enlighten both you – and Them.
How about giving this strategy a try? Like today?
Us versus Them mindset prevents synergy, learning, illumination, insight and innovation. This crippling mindset flourishes in many corporate cultures which still remain organized according to professional disciplines, departmental fiefdoms and corporate silos.
I even wrote a book of collaboration hacks so you can start poking holes in those corporate silos. Do YOU Mean Business? focuses on technical and non-technical folks collaborating to make intelligent, informed decisions on half of their clientele. Have you read it? Lately? How about a re-read?
Data scientists can work magic for your organization if you can attract and retain them. But that’s a problem.
Companies are caught between a Big Data Rock and a Data Scientist Hard Place. Companies intuitively understand the need to hire – or at least have access to – data scientists to extract relevant value from big data which impacts business outcomes. However, this is where the industrial IoT is exerting its full force on how our businesses currently are modeled.
A recent Forbes article cites an MIT Sloan Management Review study which found that only one in 5 organizations polled have changed their hiring strategy to attract and retain data scientists and analytics assets.
Between the advent of Industry 4.0 or the Fourth Industrial Revolution in 2011 and 2012, the job market for data scientists grew 15,000%, with approximately 140,000 open data scientist positions posted in 2013. Additionally, 1.5 million data literate managers will need to be re-trained or hired.
Your Rock? What your company needs to remain competitive. Your Hard Place? Status quo human capital strategy and hiring practices.
If it is within your pay grade to chew on this paradigm shift, have at it. You are overdue to come up with innovative answers to this paradox.
In the meanwhile, dip your big toe into the Big Data waters. Make data scientists your new best friends.
If you want to maintain the status quo in your organization, choose to do nothing. Unfortunately, some of the issues created by the industrial IoT and Big Data keep the C-Suite flummoxed about what to do first.
My advice: move 1 millimeter outside of your current comfort level.
Since the beginning to time, human interaction always has been a great place to start making new friends. If you do not know any data scientists, ask colleagues to introduce you. Google data science and start reading articles authored by thought leaders in the area.
Or attend meetings like the Strata+Hadoop Big Data Conference in New York City like I did last week. It is a huge meeting involving big data, machine learning and artificial intelligence experts.
Oh, did I mention that I spoke with lots and lots of data scientists about the issues which are near and dear to them and to me, as well?
You cannot move yourself, your career or your organization forward until and unless you figure out just what it is that is holding you back. Most of the time, it is your own bias and baggage about “Them.”
Move yourself forward. Start by making data scientists your new best friends. Your business acumen will explode! I promise you.
Babette Ten Haken writes, speaks and coaches about customer success for customer retention. She traverses the interface between human capital strategy for hiring and developing collaborative technical and non-technical teams. She serves manufacturing, IT and engineering intensive companies. Babette’s playbook of technical / non-technical collaboration hacks, Do YOU Mean Business? is available on Amazon. Visit the Free Resources section of her website for more tools.
Image author: laufer. Image source: Fotolia.