Random Analytica

Charts, Infographics & Analysis without the spin

Tag: Automation

Random Analytics: Mining Workforce Planning Scan (Jul 2013)

The Mining Workforce Planning Scan is a mixed quantitative/qualitative report card built from relevant online industry magazines and media sources. Utilising 14 category metrics the scan collates relevant stories over a period of time (in this case a calendar month) to give a picture of how the industry is positioned from a workforce planning perspective.

Discussing Automation (again)

Although Augmentation/Automation only had four stories for the month of July (representing 3.9% of total inputs), the subsequent robust discussion on several forums captured the attention on many industry commentators. University of Queensland’s Centre for Social Responsibility in Mining (CSRM) set off the debate when it released its Exploring the social dimensions of autonomous and remote operation mining: Applying Social License in Design report.

I discussed the subject on LinkedIn via the MiningIQ forum. It’s a lengthy discussion but my comments in relation to employment, posted 24 July 2013 included:

As welcome as this report is, I actually believe the authors are not fully recognising the full downside risks of a fully automated mining environment. Mining currently only employs around 264,000 persons (via Skills Info and correct as at Feb 2013). A cut of 50% in an open pit environment would not necessarily be picked up on the automation side, nor through large scale production increases thus you could start forecasting a peak jobs horizon for mining employment numbers in Australia in the short to medium term.

I also believe that the 50% number of open pit reductions is probably conservative. Just thinking about an Operator Hauler FIFO 14/7 shift with 3 groups in my mind’s eye I can immediately conceive of an 80% reduction as a baseline once an automated system was implemented!

I also commented on the safety issue 27 July 2013:

Within a decade I see a case where it will start to become MORE (not less) expensive, at least from an insurance perspective, to choose to operate heavy machinery with only human inputs. Let me be very clear here. As data mining becomes more commercially aware (intrusive) insurance companies will eventually overcharge or refuse to insure those industries which fail to incorporate strict augmentation and robotic controls on industries that utilise heavy equipment including miners.

Many people see automation as an all or nothing argument. That is its robotics and automated systems over all human inputs. This is not the case. My final comments on the forum, added 31 July 2013 covered that as well:

At no time has anyone on this forum discussion or myself stated that there will be no employment in mining. There will always be a requirement for onsite operational and maintenance employee’s, just the numbers will be much lower and the KSAOC’s will need to be much higher. (FYI: Knowledge, Skills, Attributes & Other Capabilities).

Megan Edwards (Editor and Director of MiningIQ) did a good write up of the main points, including some of my comments via Cost Reduction, Automation and Change Management – a Natural Trifecta? (Note: You will need a sign-on to access the story).

Here are the analytics and analysis from July.

Workforce Planning Categories

2 - Mining_Categories_Jul2013

The following chart is an 18-month look at 14 mining related workforce planning categories and the amount of times it features as a story.

Employment was the leading category with 42-stories (41.2%), the sixth consecutive month as lead category and almost unchanged in terms of weighting from the June with 38-stories (41.3%).

For the sixth month WH&S (Work Health & Safety) was the second leading category with 14-stories (13.7%). AOD/Crime was third with eight stories (7.8%).

This is the first time AOD/Crime has finished in the top 3 as a category with data going back to January 2012. Its elevation is due to a noticeable rise in incidents plus an increased willingness for mining companies to report, whereas in the past they may have not discussed these matters publically. An example of a recent incident is an act of sabotage which occurred on a Bechtel worksite on Curtis Island, Queensland. It should also be noted that the ICAC Commission did not feature in my AOD/Crime data as it never impacted on workforce planning or employment.

I’ve also included some key time periods which underline the 18-month story. July 2012 was the commencement of the commodity crash and the first phase of job and cost cutting which saw a spike in Employment related stories (mainly negative). By December 2012 the commodity prices had stabilised somewhat but off peak pricing. At the time I thought that the mining sector had returned to Business-As-Usual (BAU) but from mid-February I’ve picked up another round of job and cost cutting impacting on Employment. This second phase is currently still ongoing and deeper in terms of time period, negative sentiment and employment impact than the first round (Jul-Oct 2012).

Positive/Negative Index

3 - Mining_PosNegIndex_Jul2013

The next chart is an 18-month look at 14 mining related workforce planning categories and their positive or negative weighting.

Employment continues its highly negative trend with a further dip in July. At -18 it’s not at its worst level on record which was -20 in September 2012 but it is close enough to warrant further investigation.

At the other end of the scale Engagement recorded a +4, the tenth time in 18-months that it has been the most positive indicator.

Mining Employment Gains & Losses

4 - Mining_Employment_Jul2013

The following table looks at the employment current reported gains and losses. Reported job losses are actuals as reported by mining industry sources but often do not reflect the total loss of employment as some companies chose to limit the amount of information in relation to redundancies. Employment gains are forecast and include infrastructure phases of employment. Often employment gains are overstated as they link to public relations exercises.

July is the fourth month this year where reported employment losses were greater than 1,500. With the Queensland Resources Council stating that more than 7,000 mining jobs were lost in Queensland alone the question that I’ll be looking at later this month in a separate article will be “has mining reached its peak jobs number”.

Here’s a look at the July data.

5 - Mining_Data_Jul2013

Story of the Month

Did you know that helium is used in the production of semi-conductors and utilised for Magnetic Resonance Imaging (MRI) devices? I was not aware that the United States had a Federal Helium Reserve and that rationing of the gas has already happening. Nothing to do with workforce planning but a great article by Brent McInnes and the pick of my mining reads for July.

Final Thoughts

Last month I stated that if we had another bad set of Employment numbers in July we would be in a period similar to the commodities crash of July to October 2012.

Upon reflection I’d say that we have now exceeded the commodities crash in terms of employment friction.

Production numbers are certainly up. With more supply capacity coming on-line in coming years and some companies still locked into forward contracts (which means they are shipping commodities, namely coal at less than the total price of production) you won’t see an immediate rebound in pricing.

The risks, especially for employment are on the down side.

This is going to mean further job shedding as companies continue to tighten fiscal belts and this second phase of cost cutting looks to be ongoing, at least in the short term.

Thus more friction and workforce planning pain for both employers and employees.

Note: My previous Mining Workforce Planning Scan can be found at Random Analytics: Mining Workforce Planning Scan (June 2013).

Peak Jobs and HR Automation

During a recent recruitment discussion on #NZLEAD I brought up the concept that not only could most of the recruitment process be automated but there was a body of evidence that was proving this methodology was now successfully competing with traditional (human) practices.

What quickly became apparent was that the HR and recruitment crowd partaking in the conversation were very uncomfortable with the idea of any sort of replacement but especially by robots. A follow-up review of the #NZLEAD Recap Recruitment Processes ignored any discussion on automated process and concentrated on human inputs only.

It’s not just the recruitment process that is susceptible to an augmentation and automation overhaul. Many components of the Human Resources role could and can be downsized via augmentation or replaced by automation. It might even be argued that after automating most of the payroll function away in the 1980’s that HR itself has reached its next ‘peak job’ phase as its functions get outsourced or further automated.

So here is my ‘Good Read Guide’ on the subject of HR automation in recent times. Got one you think I have missed? Shoot me a comment with a link as I’d love to include more HR automation stories.

HR Automation – Good Read Guide

Laurie Ruettimann: Cold Reading: Sylvia Browne, Amanda Berry & Recruiters

I thought I would get kicked off with an article that sums up the topic without realms of detail and given that it’s written by the Cynical Girl it’s also a very punchy start to my reading guide. Laurie suggests that the methodology of recruitment is little better than an “unsophisticated psychic trick”: and “that technology can solve for bias and discrimination in the hiring process”.

Naomi Bloom: HRM Analytics – Dashboards, Cockpits And Mission Control

1 - NaomiBloom_1992

One item that keeps coming up in my ongoing conversation with HR is that I believe all things can be measured (but not all things should be as you should look for value against effort). There is always lots of discussion about this in the HR space. Naomi Bloom believes that all things HR should be measured. In an earlier 2009 piece she stated:

“If the real purpose, the only purpose, of HRM is to achieve organizational outcomes, then we’d better be able to measure the effects of specific investments in HRM on those organizational outcomes. Otherwise, why would anyone trust us with a budget?”

I reached out via Twitter to Naomi Bloom, given that she has spanned the entire modern HR journey between old and new (the picture is a copy of her 1992 opus on the subject which she kindly sent me). She suggested the above recent analytics article as a primer. It’s worth a read given that analytics is a key augmentation step and who does robots better than NASA!

The Ladders: Keeping an eye on recruiting behavior

Here is a resume service provider using eye tracking technology to highlight where recruiters spend their “four to five minutes per resume”. Don’t think resume writing or reviewing can be automated…. Think about it as a series of transactions and then ask yourself, can each of these transactions become automated?

Fiona Smith (via the Australian Financial Review): Driven by data: moneyball recruitment takes away all the guesswork

On the subject of recruitment Carol Howard suggested this piece by Fiona Smith on using data and analytics to take the guess work out of the hiring process. The case study utilised is Sears Holdings Corporation which put all of its applicant data against its employee data and found that their “best employees did not come from their previous talent pool”. If robots aren’t in the process of taking over the job of recruiters, big data is certainly going to assist in the downsizing of that role.

John Sumser: The perils of Automation

Before I leave you with links to a HR future that might not need (much less) humans in it I came across this thoughtful 2012 piece by John Sumser. Very wisely John suggests that “Automation strips the fuzzy stuff out of relationships to turn them into transactions. In that process, things get much more efficient. It’s less clear that we understand what we’re leaving behind.

David Creelman (via HRVoice.org): Unending Automation

Maybe the role of HR won’t be in looking after your current employee’s but assisting those who are technologically displaced prior to their own exit. David Creelman suggests:

“Many countries do not require organizations to protect workers from technological change. If self-driving vehicles can replace your truckers then perhaps you can just send them a note wishing them luck finding another job. However, ethically we have a responsibility to at least inform workers about their longer-term prospects and preferably find ways to help. Ways to help could include early retirement, job-sharing, or retraining. HR should explore all those options.”

Steve Boese: Virtual HR, or, ‘Did you ask the HR chatbot’

2 - Ivy

My final link (and my favourite) is from Steve Boese, not only a HR technology professional but also someone with a keen interest in how technology is transforming work. In this blog Steve looks at Intel’s incorporation of Ivy, the virtual HR agent who at the time of publishing could respond in 4,331 ways to staff interactions. On the subject of HR automation Steve states:

“Most of us, (admittedly me too), say of think things like ‘My job is just too complex and ever-changing for it to even be outsourced to a less-expensive human (much less a robot).’

The criticism of this potential HR future was summed up nicely by David Gordon, a recruiter, who replied to my original tweet/link with “@gmggranger it is a good read – still not fit for purpose for recruitment (yet?!), Ivy answers factual questions, recruitment is subjective”.

I’ll agree with you David (at the moment). Yet, a journey starts with a single step…

Final Thoughts

Human Resources are being asked to assist in the transition of human workforces to augmented or automated workplaces. From automated trucks in the mines, DIY checkouts at the supermarket or robotics augmenting people on the factory floor every industry is under increasing competitive pressure.

Yet HR itself seems totally against a conversation about HR automation.

I get it. You’re a knowledge worker and the things that you do for the organisation are just too complex to be replaced by SkyNet.

But maybe its time for HR to review this thinking. As Steve Boese states:

But it also seems likely that given enough time, access to ever-improving technologies, and the right economic incentives, there are enterprising people and organizations that even if they couldn’t completely automate or robot-icize everything you do, chances are a fair amount of even what we creative types do is already routine enough that the robots could do a passable, if not better (and cheaper and will less of a bad attitude), than we do.”

The kind of hollowing out of HR, last seen when payroll was automated from the 1980’s is already starting to impact on the HR function and recruitment seems to be the current automation focal point.

Better start getting involved in the conversation people!

It’s going to happen with or without you.

 

Acknowledgements: In an effort to shine some light on this subject I started tweeting HR automation stories from various writers. My twitter-sphere colleague Michael Carty of XpertHR suggested it might be good to compile these into a single resource. Great idea Michael and I hope you like the post!

Special Note: For those who have not read any of my previous articles on peak jobs and need a little background. ‘Peak Jobs’ is the idea that technology is replacing jobs faster than it’s creating them. For those more technically inclined it can also be attributed to the finalisation of the increased growth in average output (and income) per labour unit due to technological change since the 1820’s as put forward by Robert Solow (1956) or the commencement of technological unemployment as put forward by John Maynard Keynes (in the 1930’s) without the opportunity to transition into new roles as productivity increases but global employment declines.

Random Analytics: Mining Workforce Planning Scan (Apr 2013)

Robotic Replacement expands in Australia

I spend a lot of time analysing either the stories with the most content or with the most positive or negative impact. Some categories don’t get the coverage in terms of either content or impact that they deserve.

Although it only had two stories for the month of April the indicator Augment(ation), which tracks all things to do with work augmentation, automation and robotic replacement was the category with the most impact.

The first story was the announcement that Hitachi will commence trailing automated trucks at the Meandu coal mine in the between the Sunshine Coast and Wide Bay Burnett regions of Queensland (just 2-hours north-west of Brisbane). The first three EH5000 AC trucks were expected to arrive by the end of April with Stanwell running trails over the next three-years. This is also the first real robotic replacement deployment in Queensland within range of the most extensive coal deposits in Australia (the Bowen and Galilee Basins) and is an ideal recce for Hitachi who has plans to develop more autonomous equipment to the surface mining industry by 2017 (as some of the larger projects in Queensland come on-line).

The second story was a robotics replacement milestone reached in Western Australia. Rio Tinto announced that its driverless trucks had now moved more than 100-million tonnes from its West Angelas, Yandicoogina, and more recently the Nammuldi operations. That’s almost double the amount Rio moved when it featured on the 7.30 Report (21 Feb 2012) stating it had moved 57-million tonnes.

All of this as BIS Shrapnel revised its engineering and construction numbers down from its 2012 report, stating that the nadir will commence from 2014 and not 2015. Mining doesn’t employee big numbers compared to other sectors when in its operations phase, it does however employee big exciting numbers during its infrastructure phase (which is currently still ongoing). Anecdotally, I had a conversation with a colleague who runs a Job Services Australia office who told me that the only ‘tradie’ (Australian slang for construction worker) he has seen since 2008 are those who have lost their license.

1 - Mining_AutomatedMiningTruckSites_Apr2013

Categories

For the third consecutive month Employment was the leading category with 27-stories (32.9%) more on job cutting than employment creation this month. WH&S (Work Health & Safety) followed with 22-stories (26.8%) while IR (Industrial Relations) finished third with 9-stories (11%) after a quiet March.

No stories were recorded for AOD/Crime (Alcohol & Other Drugs) or SkillsShort (Skills Shortages) in April.

2 - Mining_Categories_Apr2013

Positive/Negative Index

With one positive and seven negative stories WH&S, at minus 6 was the most negative indicator for April. The articles included at least four significant injuries and another site-death; this time of a contractor who collapsed at the Wesfarmers owned Curragh Coal Mine.

After six positive stories, L&D/R&D (Learning & Development/Research & Development) finished as the most positive with plus 6, the best monthly positive indicator for the first four months of 2013. The stories included the mining industry detailing its $1.15Bn (AUD) spend on training over the past two years, updates on two new mining training facilities and the donation by the New Gold Peak Mine of a $100,000 dollar underground loader to Western Dubbo TAFE.

On that story, I wonder if I’ll be recording a negative input next year as Western Dubbo TAFE realises no CAPEX spend but several thousand dollars in ongoing maintenance and WH&S implementation costs.

3 - Mining_PosNegIndex_Apr2013

Mining Employment Gains & Losses

Although April saw another good set of employment numbers discussed there was also a loss of both actual and prospective positions headlined by Arafura Resources which pulled out of its proposed Whyalla Rare Earths processing plant. This development may have delivered 1,000 jobs and $1-billion in economic development to the South Australian economy.

On the positive side Rio Tinto Alcan talked up the prospects of building its bauxite mine near Weipa later this year (950 construction workers during infrastructure phase, with 1,346 total employees including contractors forecast for operations) and Gindalbie opening its Karara iron ore project (500 operation jobs).

Technical note: I have updated the February employment numbers, shifting 400 from February to April as NRW Holdings announced the signing of works on the Nummuldi iron ore mine. Overall the project was forecast to employ 1,500 during the infrastructure phase.

4 - Mining_Employment_Apr2013

Here’s a look at the April data.

5 - Mining_Data_Apr2013

Story of the Month

Fortescue Metals Group (FMG) announced this month that it would be replacing its ‘spread-sheet’ system of rostering (and managing labour costs no doubt) with Microster with the implementation to be managed by ComOps.

FMG owes around $12.6-billion dollars (roughly 4.7% of Australia’s Total Commonwealth Government Securities on Issue) and employs more than 2000 employees and is managing its labour by the manual manipulation of ‘Busted Ass Spread Sheets’ (BASS).

Hard to believe, but true.

Final Thoughts

I choose the term ‘robotic replacement’ with the full knowledge that many are uncomfortable with the term. It should be noted that both stories mentioned in the introduction either emphasise safety or integration with employees while avoiding the subject of technological replacement of human workers or even peak mining employment.

It’s a common stratagem of lots of organisations when dealing with problematic issues.

Yet, we are beyond imaging what the mine of the future is as it is already here and being deployed more progressively as each year passes. Western Australian and Queensland deployments this year, no doubt New South Wales or the Northern Territory next.

Australians are just going to have to get used to the gradual transition to the mine of the future. That future is one which is largely operated by robotics and technology by a limited number of highly skilled personnel, potentially from any point on the globe.

 

Note: My previous post on Mining Workforce Planning Scans can be found at Random Analytics: Mining Workforce Planning
Scan (Mar 2013)