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Don’t Let Today’s Demands Kill Tomorrow’s Workforce – Stratacom – San Jose May 27, 2015

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Don’t Let Today’s Demands Kill Tomorrow’s Workforce – Stratacom – San Jose

Feb, 2015

Martin Waterhouse – Enterprise IT Strategist

So much for my “working vacation” I never expected to be here 33 years!

From mainframes to mobiles, application development to architecture, databases and directories to cybersecurity, I have held a myriad of IT roles for the energy sector for 33 years witnessing  significant changes in the rate of change in technology plus the capabilities of the workforce needed to support it. My swansong role was as a strategist seeking ways to help prospective IT experts navigate a career path through the murky waters of today’s energy company IT organization.

A long long time ago in an alley not so far away ….

In 1978 the oil price was around $15 a barrel, by 1982 the benchmark oil price had risen to around the $30-35 a barrel then dropped way down to $23 in January 1986.

https://drive.google.com/open?id=1Suz3Ipcj-y9dljOEBMzhFWBS6rYbVYJc6aYG0FTNWLw&authuser=0

I can possibly even attribute my recruitment as the result of this significant uptick in the price of oil. By 1981 Standard Oil of California, desperate to find a number of experienced PL/1 programmers and unable to find them in the US ending up looking 6000 miles away in the UK.

During the first decade I noticed that every time there was a spike or crash in the oil price, capital projects and operational personnel were significantly impacted. Merger and acquisition activity associated with financial turmoil amplified these effects. At the time, there tended to be a lower impact on technical services and R&D functions especially in IT roles. Many non-IT personnel made an effort to join the IT service company with its apparent promise of more stability for long-term development of technical careers.

The second decade culminated in the rise and fall of the dot-com bubble where we were increasingly desperate to develop and retain IT talent, especially in the San Francisco Bay Area. Some areas were severely impacted requiring a large influx of contract staff. Following a merger with Texaco, we were increasingly reliant on outsourcing, offshoring and the start of a shift of services away from California to Texas. Thus began some of today’s challenges of technical continuity in the IT space.

In the last decade, the reaction to oil-price and shareholder pressure has become even more acute with uncertain IT stability and an even greater pressure to commoditize and virtualize IT services. An even greater challenge is how to be recognized in developing and sustaining a consistent depth,  breadth of IT knowledge and related value applied to the myriad of energy company applications.

Big Data: The lifeblood of an Energy company.

The data science areas may have the most significant impact. One of my former managers Peter Breunig gave this presentation for IBM at their Almaden research lab:

Managing More Bits Than Barrels

A small citation from this presentation really puts things in perspective, Chevron has a long history in big data especially in the seismic data processing and core sample analysis. For example the micro-pore analysis for 1 cubic centimeter of a core sample can create over 100GB of data. Just a single sample analysis on a full 1000M core sample can generate over an Exabyte of storage!

Traditional long careers in Chevron IT: In Jeopardy?

What does this do to the sense of value for long-term technical career, of technical excellence, a sense of permanence, a viable, engaging learning trajectory and corporate loyalty? Perhaps in the core aspects of the energy industry in general. What of the IT space?

By 2015, with the burden of further downside oil-price pressure, Chevron IT appears to be taking an ever decreasing short-cycle strategy making it much harder to enable long-term technical skill career trajectories and technology deliverables.

With an industry trend to continue to commoditize services, increasing use of consumer/BYOT platforms and general shorter expected tenure the likelihood of many future generation IT “lifers” is in jeopardy. I’m not saying this is a bad thing but I wonder how prepared we (a large energy multinational) are to deal with some of the long-term consequences in sustaining the talent pipeline supporting our “crown-jewel” areas of IT expertise.

Is there still value in “Firm-specific human capital”.

Are we going to continue to erode the long-term human-capital knowledge?

On the plus side, we have some lively internal communities attempting to feed and grow big-data expertise, data scientists and modeling experts. Led by one of our IT Fellows, the modeling and analytics community certainly has an opportunity to keep the spotlight on this area.

Potential Enterprise Data/Modeling and Analytics Communities of practice:

  • Seismic processing
  • Oilfield production analysis and modeling (iField)
  • Optical sensor analysis
  • Down-hole sensor log processing
  • Drilling analysis and monitoring
  • Rotating machinery operational sensing/modeling
  • Stock-flow modeling
  • Global O&G Economic modeling
  • Pipeline flow analysis
  • HVAC monitoring
  • Buildings and Facilities Electrical system simulations
  • Cyber security anomaly detection
  • Perimeter security monitoring and analysis
  • Marketing trends analysis
  • Environmental airflow modeling
  • Environmental remediation analysis
  • Catalysis, Fuels Research, Molecular modeling
  • Materials/Lubricants R&D  Science
  • Emergency response modeling
  • Organizational Capability/HR technical talent simulation

…. not to mention emerging areas of interest we may not yet be aware of that can derive significant value.

It seems we are clearly in a time of highly disruptive change with regards to technical careers, are we going to be able to rely on an ample supply of modeling & analytics, big data and visualization experts?  How do we engage and educate them in the aspects and peculiarities of the energy sector to enable them to realize value?

How will our hiring practices need to evolve to seek out potential data science experts and then manage to keep them through bleak fiscal times?  Clearly, giving them opportunities to  improve their craft, seek diversity and embed themselves into the business is crucial. Countering this is the ever constricting budgets

How will any large enterprise sustain and justify the cost to sustain a talent pipeline to connect the qualified data source and business application experts to them?

…. to be continued …..

In the meantime, here’s a data-science HR challenge – think of creative ways to capture and sustain quality metrics to support (or refute) the findings from the value of human capital? This 2003 research paper is considered a bellwether publication. Is the model even valid more than a decade later when the average tenure of many technologists today appears to be an order of magnitude shorter?

A 2003 paper from the National Bureau of Economic Research (Edward P. Lazear Stanford University):

Firm-Specific Human Capital: A Skill-Weights Approach

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