Artificial Intelligence – Explaining the Unexplainable

Posted on : 23-09-2019 | By : kerry.housley | In : Finance, FinTech, General News, Innovation

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The rise of Artificial Intelligence (AI) is dramatically changing the way businesses operate and provide their services. The acceleration of intelligent automation is enabling companies to operate more efficiently, promote growth, deliver greater customer satisfaction and drive up profits. But what exactly is AI? How does it reach its decisions? How can we be sure it follows all corporate, regulatory and ethical guideline? Do we need more human control? 

Is it time for AI to explain itself? 

The enhancement of human intelligence with AI’s speed and precisiomeans a gigantic leap forward for productivity. The ability to feed data into an algorithm black box and return results in a fraction of the time a human could compute, is no longer sci fi fantasy but now a reality.  

However, not everyone talks about AI with such enthusiasmCritics are concerned that the adoption of AI machines will lead to the decline of the human role rather than freedom and enhancement for workers.   

Ian McEwan in his latest novel Machines Like Me writes about a world where machines take over in the face of human decline. He questions machine learning referring to it as

“the triumph of humanism or the angel of death?” 

Whatever your view, we are not staring at the angel of death just yet!  AI has the power to drive a future full of potential and amazing discovery. If we consider carefully all the aspects of AI and its effects, then we can attempt to create a world where AI works for us and not against us. 

Let us move away from the hype and consider in real terms the implications of the shift from humans to machines. What does this really mean? How far does the shift go?  

If we are to operate in world where we are relying on decisions made by software, we must understand how this decision is calculated in order to have faith in the result.   

In the beginning the AI algorithms were relatively simple as humans learned how to define them. As time has moved on, algorithms have evolved and become more complex. If you add to this machine learning, and we have a situation where we have machines that can “learn behaviour patterns thereby altering the original algorithm. As humans don’t have access to the algorithms black box we are no longer in charge of the process.   

The danger is that where we do not understand what is going on in the black box and can therefore no longer be confident in the results produced.

If we have no idea how the results are calculated, then we have lost trust in the process. Trust is the key element for any business, and indeed for society at large. There is a growing consensus around the need for AI to be more transparent. Companies need to have a greater understanding of their AI machines. Explainable AI is the idea that an AI algorithm should be able to explain how it reached its conclusion in a way that humans can understand. Often, we can determine the outcome but cannot explain how it got there!  

Where that is the case, how can we trust the result to be true, and how can we trust the result to be unbiased?  The impact of this is not the same in every case, it depends on whether we are talking about low impact or high impact outcomes. For example, an algorithm that decides what time you should eat your breakfast is clearly not as critical as an algorithm which determines what medical treatment you should have.  

As we witness a greater shift from humans to machines, the greater the need for the explainability.  

Consensus for more explainable AI is one thing, achieving it is quite another. Governance is an imperative, but how can we expect regulators to dig deep into these algorithms to check that they comply, when the technologists themselves don’t understand how to do this. 

One way forward could be a “by design” approach – i.e., think about the explainable element at the start of the process. It may not be possible to identify each and every step once machine learning is introduced but a good business process map will help the users the define process steps.  

The US government have been concerned about this lack of transparency for some time and have introduced the Algorithmic Accountability Act 2019. The Act looks at automated decision making and will require companies to show how their systems have been designed and built. It only applies to the large tech companies with turnover of more than $50M dollars, but it provides a good example that all companies would be wise to follow.  

Here in the UK, the Financial Conduct Authority is working very closely with the Alan Turing Institute to ascertain what the role of the regulator should be and how governance can be  appropriately introduced.

The question is how explainable and how accurate the explanation needs to be in each case, depending on the risk and the impact.  

With AI moving to ever increasing complexity levels, its crucial to understand how we get to the results in order to trust the outcome. Trust really is the basis of any AI operation. Everyone one involved in the process needs to have confidence in the result and know that AI is making the right decision, avoiding manipulationbias and respecting ethical practices. It is crucial that the AI operates within public acceptable boundaries.  

Explainable AI is the way forward if we want to follow good practice guidelines, enable regulatory control and most importantly build up trust so that the customer always has confidence in the outcome.   

AI is not about delegating to robots, it is about helping people to achieve more precise outcomes more efficiently and more quickly.  

If we are to ensure that AI operates within boundaries that humans expect then we need human oversight at every step. 

The Challenges of Implementing Robotic Process Automation (RPA)

Posted on : 25-01-2019 | By : kerry.housley | In : Innovation, Uncategorized

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We recently surveyed our clients on their views around the future of technology in the workplace and the changes that they think are likely to shape their future working environment. 

One of the questions identified by many clients as a major challenge was around the adoption of RPA. We asked the question; 

“Do You Agree that RPA could improve the Efficiency of Your Business? 

Around 65% of the respondents to our survey agreed that RPA could improve the efficiency of their business, but many commented that they were put off by the challenges that needed to be overcome in order for RPA deployment to be a success. 

“The challenge is being able to identify how and where RPA is best deployed, avoiding any detrimental disruption 

In this article we will discuss in more detail the challenges, and what steps can be taken to ensure a more successful outcome. 

The benefits of RPA are:

  • Reduced operating costs
  • Increased productivity
  • Reduce employee’s workload to spend more time on higher value tasks
  • Get more done in less time! 

What Processes are Right for Automation? 

One of the challenges facing many organisations is deciding which processes are good for automation and which process to choose to automate first. This line from Bill Gates offers some good advice; 

automation applied to an inefficient operation will magnify the inefficiency” 

It follows therefore, that the first step in any automation journey is reviewing all of your business processes to ensure that they are all running as efficiently as possible.  You do not want to waste time, money and effort in implementing a robot to carry an inefficient process which will reap no rewards at all.  

Another challenge is choosing which process to automate first. In our experience, many clients have earmarked one of their most painful processes as process number one in order to heal the pain.  This fails more often than not because the most painful process is often one of the most difficult to automate.  Ideally, you want to pick a straightforward, highly repetitive process which will be easier to automate with simple results, clearly showing the benefits to automation. Buy-in at this stage from all stakeholders is critical if RPA is be successfully deployed further in the organisation. Management need to see the efficiency saving and employees can see how the robot can help them to do their job quicker and free up their time to do more interesting work. Employee resistance and onboarding should not be underestimated. Keeping workers in the loop and reducing the perceived threat is crucial to your RPA success.  

Collaboration is Key 

Successful RPA deployment is all about understanding and collaboration which if not approached carefully could ultimately lead to the failure of the project.  RPA in one sense, is just like any other piece of software that you will implement, but in another way it’s not. Implementation involves close scrutiny of an employee’s job with the employee feeling threatened by the fact that the robot may take over and they will be left redundant in the process.   

IT and the business must work closely together to ensure that process accuracy, cost reduction, and customer satisfaction benchmarks are met during implementation.  RPA implementation success is both IT- and business-driven, with RPA governance sitting directly in the space between business and IT. Failure to maintain consistent communication between these two sides will mean that project governance will be weak and that any obstacles, such as potential integration issues of RPA with existing programs, cannot be dealt effectively. 

Don’t Underestimate Change 

Change management should not be underestimated, the implementation of RPA is a major change in an organisation which needs to be planned for, and carefully managed. Consistently working through the change management aspects is critical to making RPA successful. It is important to set realistic expectations and look at RPA from an enterprise perspective focusing on the expected results and what will be delivered. 

 RPA = Better Business Outcomes 

RPA is a valuable automation asset in a company’s digital road map and can deliver great results if implemented well. However, often RPA implementations have not delivered the returns promised, impacted by the challenges we have discussed. Implementations that give significant consideration to the design phase and realise the importance of broader change management into the process will benefit from better business outcomes across the end-to-end process. Enterprises looking to embark on the RPA journey can have chance to take note, avoid the pitfalls and experience the success that RPA can bring. 

Are you ready to take advantage of Robotic Process Automation?

Posted on : 28-02-2018 | By : richard.gale | In : Innovation, Uncategorized

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Robotic Process Automation or RPA is growing fast. We were initially sceptical as to how innovative it actually is but are always looking for ways to help our clients (and Broadgate!) work more efficiently.

RPA technology, sometimes called a software robot or ‘bot’, mimics a human worker, logging into applications, entering data, calculating and completing tasks, and logging out.

RPA software isn’t really part of an organisation’s IT infrastructure. It sits above, enabling a company to implement the technology quickly and efficiently without changing the existing infrastructure and systems.

RPA could be seen as a ‘tactical’ approach to solving a business problem. In the long term the ‘bots’ should be replaced by strategic solutions but the advantages of quickly being able to make a process more efficient and remove human error can make immediate efficiency gains. And we all know how long these tactical solutions can remain in place….

The evolution of RPA

Although the term “robotic process automation” can be traced to the early 2000s, it had been developing for a number of years previously. We worked on screen scraping applications in the early ’90s to help turn ‘green screens’ into newly fashionable GUI applications.

RPA evolved from three key technologies: screen scraping (mimicking user interaction), workflow automation and artificial intelligence.

Screen scraping is the process of collecting screen display data from a legacy application so that the data can be displayed by a more modern user interface. The advantages of workflow automation software, which eliminates the need for manual data entry and increases order fulfilment rates, include increased speed, efficiency and accuracy. Lastly, artificial intelligence involves the ability of computer systems to perform tasks that normally require human intervention and intelligence.

Benefits of RPA

Robotic process automation technology can help organisations on their digital transformation stories by:

  • Creating cost savings for manual and repetitive tasks
  • Enabling employees to be more productive
  • Enabling better customer service
  • Ensuring business operations and processes comply with regulations and standards
  • Allowing processes to be completed much more rapidly
  • Providing improved efficiency by digitising and auditing processes

Applications of RPA

Some of the applications of RPA include:

  • Financial services: Companies in the financial services industry can use RPA for foreign exchange payments, automating account openings and closings, managing audit requests and processing insurance claims.
  • Customer service: RPA can help companies offer better customer service by automating call centre tasks, including verifying e-signatures, uploading scanned documents and verifying information for automatic approvals or rejections.
  • Accounting: Organisations can use RPA for general accounting, operational accounting, transactional reporting and budgeting.
  • Supply Chain:  RPA can be used for procurement, automating order processing and payments, monitoring inventory levels and tracking shipments.
  • Healthcare: Medical organizations can use RPA for handling patient records, claims, customer support, account management, billing, reporting and analytics.
  • Human resources: RPA can automate HR tasks, including onboarding and offboarding, updating employee information and timesheet submission processes.

 

What’s so different from regular automation?

What distinguishes RPA from traditional IT automation is the ability of the RPA software to be aware and adapt to changing circumstances, exceptions and new situations.
Once RPA software has been trained to capture and interpret the actions of specific processes in existing software applications, it can then manipulate data, trigger responses, initiate new actions and communicate with other systems autonomously.
RPA software is particularly useful for organisations that have many different and complicated systems that need to interact together fluidly.
For instance, if an electronic form from a Compliance system (such as know your customer) is missing a postcode, traditional automation software would flag the form as having an exception and an employee would handle the exception by looking up the correct postcode and entering it on the form. Once the form is complete, the employee might send it on to Compliance so the information can be entered into the approved customer system.
With RPA technology, however, software that has the ability to adapt, self-learn and self-correct would handle the exception and interact with the payroll system without human assistance.

What to look for in RPA software

When enterprise leaders look for RPA technologies, they should consider a number of things, including:

  • Simplicity: Organisations should look for products that are simple enough that any employee in the business can build and use them to handle various kinds of work, including collecting data and turning content into information that enables leaders to make the best business decisions.
  • Speed: Enterprises should be able to design and test new robotic processes in a few hours or less, as well as optimise the bots to work quickly.
  • Reliability: As companies launch robots to automate hundreds or even thousands of tasks, they should look for tools with built-in monitoring and analytics that enable them to monitor the health of their systems.
  • Intelligence: The best RPA tools can support simple task-based activities, read and write to any data source, and take advantage of more advanced learning to further improve automation.
  • Scalability: Organisations shouldn’t select RPA software that requires them to deploy software robots to desktops or virtualised environments. They should look for RPA platforms that can be centrally managed and scale massively.
  • Enterprise-class: Companies should look for tools that are built from the ground up for enterprise-grade scalability, reliability and manageability.

Prerequisites for robotic process automation

  1. Are you able to describe the work? This doesn’t mean your documentation exists or is current. The task could be described by recording a user performing their work on a computer including how they handle exceptions.
  2. Is the work rules-based rather than subjective? Robots need to be prepared (aka, taught, trained, configured) to perform specific actions on your systems. Current technology is insufficient for a robot to determine on its own what to when faced with a new situation.
  3. Is the work performed electronically? It doesn’t matter how many different applications are required or whether they are in-house, cloud-based, Citrix, desktop or mainframe.
  4. Is the required data structured (or could it be structured)? If not, you may be able to utilise an OCR and/or cognitive application capable of structuring the file.  Alternatively, you could have people enter the data into a structured format.

Disqualifiers for robotic process automation use cases​​

  1. Process stability. If your organisation keeps changing the process (e.g., responding to competitive factors or new sources of information), then it may not be the right time to automate it. Despite investing resources to stabilise the current activity, you may end up with too much maintenance to keep your automation aligned to business needs.
  2. Target applications suitability. Some applications are harder for robots to use than others. It’s a fact that vendors don’t really like to highlight in the sales process. Starting with an especially challenging target application could delay the whole program, cause fatigue in leadership and put your credibility at risk. If you have to do it, make sure that you build in an accurate view of the time required.

Organisational impacts of RPA

Though automation software is expected to replace up to 120 million full-time employees worldwide by 2024, many high-quality jobs will be created for those who maintain and improve RPA software.

When software robots do replace people in the enterprise, managers need to be responsible for ensuring that business outcomes are achieved and new governance policies are met.

Robotic process automation technology also requires that the CIO take more of a leadership role and assume accountability for the business outcomes and the risks of deploying RPA tools.

Additionally, the COO, CIO and HR, as well as the relevant executive who owns the process being automated, should all work toward ensuring the availability of an enterprise-grade, secure platform for controlling and operating bots across systems.

Where the robotic process automation market is heading

One report expects the RPA market to reach $5 billion by 2024. The increased adoption of RPA technologies by organisations to enhance their capabilities and performance and boost cost savings will reportedly drive the growth of the robotic process automation market most during that time.

We are excited that the mix of technologies and domain business expertise will enable this growth and we are focusing on growing our skills in this area.

Featured Tech Startup – Interview With Allan Martinson, Starship Robots

Posted on : 26-04-2016 | By : Maria Motyka | In : 5 Minutes With, Cyber Security, Featured Startup, General News, Innovation, IoT

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What is it like to be part of a startup which brings robots to life (and to the streets of London)?

Our robots have been named #4 most anticipated tech product of 2016, right after Apple’s new iPhone. It is totally awesome!!! I have been part of many companies in my life but this one has completely spoiled me. It is such a ride.

 

starship woww

 

Starship Robots was featured in Forbes’ first episode of ‘The Premise’ tech podcast, during which one of the co-founders of Starship noted that the delivery industry is the largest undisrupted industry in the world and stated that “Millions of parcels are being delivered every day in a wasteful manner and its possible to automate this using today’s technology”. Could you please expand on this?

In EU and US alone the delivery firms carry 25 billion packages a year, plus we are doing 130 billion shopping trips on our cars. There is absolutely no point of moving a 2 or 7 ton gas-guzzling vehicle to bring somebody a few kilos of deliveries. You better put wheels to this package or bag and let it roll to you, with 0 emissions, 0 noise, 0 road congestion.

An average family loses an hour per day on shopping trips. We have a mission of giving people this 1 hour back. You can do your own math how many billions of hours we could release.

 

What do you consider as the most interesting insight you have learnt during Starship Robots’ trials? How prepared are consumers for their adoption?

People are MUCH more friendly towards those devices than we ever thought. And absolute majority takes them as the most natural thing on Earth.

 

starshipp

 

Each of Starship’s innocent-looking robots is equipped with 9 cameras, providing you with a 360 perspective. How would you respond to concerns over data privacy linked to what some could consider the introduction of surveillance machines to the streets and people’s doorsteps?

What is the difference between a driven looking at surroundings through the car’s window and our operator (potentially) looking at the sidewalk through cameras? Nothing. Following your logic, we should drive cars with closed eyes 🙂

 

As someone working in new tech, how do you imagine European metropolises in 10, 20 years?

European cities in 20 years will have self-driving cars and around 3 delivery robot per each such car. That is not a joke but based on our calculation on transportation needs.

 

When can we expect a launch of Starship Robots?

We expect a full launch in 2017. BTW We are looking for a name for the robot and feel free to submit ideas on www.starship.xyz.

Is a robot also in line for your next interview?

Posted on : 26-02-2016 | By : Maria Motyka | In : Innovation, Uncategorized

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The consignment to history of what were key jobs at the time is, of course, a natural consequence of technological advancement (see our previous article on the future resource market). Replaced by ‘new’ tech of the time, everything from switchboard and elevator operators to “ice cutters” have their place in the list of professions which have long since left our daily job boards.

Nevertheless, over the past few years there has been an increased amount of coverage given to the consequences of new tech and the 4th Industrial Revolution (including by leaders at last month’s World Economic Forum), which is said to lead to jobs currently held by men and women becoming filled by machines in pretty much every sector and industry in the global economy.

Thomas Frey, Senior Futurist at the DaVinci Institute, and Google’s top rated Futurist Speaker, predicts that by 2030 a whopping 2 billion jobs will no longer exist (to put that in context… around half of all the jobs on the planet). Does this mean that we have a 50 per cent chance of becoming jobless within the next few decades, because of automation and other new technologies, such as robots being introduced?

robot

Worry not!…apparently the answer is no.

According to Frey, what it means is that our jobs are transitioning, and it is happening “at a higher pace than ever before in history”. The futurist stresses that due to their catalytic nature, several innovations, including driver-less cars, teacher-less education and 3D-printable houses, are actually going to create completely new industries. This view is supported by a recent report, Fast Forward 2030: The Future of Work and the Workplace, which states that;

“Losing occupations does not necessarily mean losing jobs – just changing what people do”, and by Principal Researcher at Microsoft Research, Jonathan Grudin, who said that “Technology will continue to disrupt jobs, but more jobs seem likely to be created”

As an example, let’s take 3D printing, which Chris Anderson, Managing Editor of Wired Magazine believes to be even bigger than the Internet. Frey predicts, that as 3D printing matures, professions such as clothing manufacturing and retailing, as well as lumber, rock, drywall, shingle and concrete industries are going to disappear. However, new jobs will become available in the areas of 3D printer design, engineering and manufacturing (although, in one scenario a 3D printer can print a baby 3D printer); there will be a demand for 3D printer repairmen, product designers, stylists, engineers and ‘ink’ sellers.

While predicting that even though robots will fill some jobs, others will benefit from this productivity growth and subsequently will have more income and more disposable income. This in turn will increase the need for other jobs. Heidi Shierholz, Chief Economist at the U.S. Labor Department, implies that the pace of change might at times be exaggerated. During the Will your Job Disappear by 2024? Bloomberg Benchmark podcast she stated that actually we are not seeing a massive acceleration in productivity, which would signal that robots and automation have some way to go in removing the levels of workforce that some are predicting. Indeed, while historically productivity has grown around 2 per cent a year, over the last 10 years it has actually been a little bit slower.

Are we being over dramatic about the speed of the changes leading to an increased man vs machine conflict in the workplace? All we can say for certain is that whilst the more extreme scenarios are increasingly likely to make headlines and reach your feeds, it is certain that sooner or later technology will change your job and those of the next generation.

Innovation and the impact on future jobs

Posted on : 28-08-2015 | By : john.vincent | In : Innovation

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For those of us who started our careers last century, the pace of change and innovation over the past decade is astounding. After life settled down somewhat following Y2K, the first internet bubble and a heightened period of world turmoil, we are “back to the future” full steam (click here for any film fans that missed the hoverboard release a while back).

Innovations in robotics, blockchain technology, the internet of things, automation and so on is transforming our world to a point that in 20-30 years the way we live and interact within it will be a step change away from today.

So, rather than opine about where these innovations may end up, let’s have a think about one of the side effects…most notably, on jobs.

Those of us that are lucky enough to enjoy our work (and are of a certain age) are probably doing something not that dissimilar to when we left education. Indeed, when I took my first role in technology at a bank it was still considered to be “a job for life”. I could happily start planning for a life on the greasy pole and a final salary pension in a max of around 4 decades of grafting.

Fast forward to today and for those entering the employment market things are very different. That concept now seems so old fashioned. The characteristics possessed by careers of being stable, linear and mainly singular are gone. So what can the next generation of workers expected? Renowned futurist Thomas Frey of the DaVinci Institute is quoted as saying;

60% of the best jobs in the next ten years haven’t been invented yet.

This naturally has a huge impact. Careers will become a polymorphic thing, increasing in complexity, reducing in predictability and will evolve for many into a “portfolio of micro-careers”. Innovation and commoditisation will mean that being able to move laterally between roles and industries will be the norm, with an entirely different mindset and skillset being required to maintain personal “career currency”.

We are already starting to live in the world of the freelancer. Shorter term, output based contracts are on the rise with estimates that by 2020 half of all workers in the US will be freelance and even now, some 20% of UK graduates are joining the labour market in the same capacity. Assuming this trend continues, the impact on traditional employee management, such as performance, reward, culture etc. is something that organisations will need to overcome. Indeed the word “employee” may be used sparingly in favour of “workforce”.

So what are the types of jobs that we might see in the future? Here are a few examples (that 10 years ago would have been considered daft);

  • Alternative Currency Speculator: With Bitcoin and other virtual currencies gaining ground, new more complex trading asset classes will also evolve
  • 3D Printing Manager: Expert roles in 3D printing to help consumers build new or repair current physical artefacts
  • Privacy Consultant: A role to reveal vulnerabilities in an individuals personal, physical, and online security presence
  • Drone Driver: As the deployment expands outside of the military to commercial and private drone use, experienced drone drivers (especially those with urban experience) will be sought after
  • Crowdfunding Manager: A expert on sites like Kickstarter and Crowdcube who provide clients services to promote and attain funds for a project
  • Digital Death Manager: Someone who manages or eliminates some digital footprint and creates a posthumous online presence
  • Meme Agent: We know all too well that we have agents for every kind of celebrity, so in the future, even stars on internet memes will be represented

(If you want to see a list of jobs that might disappear all together (and of course find yours…), click here for a list of 101 Endangered Jobs by 2030

And what about the impact of robotics? Whilst we are indeed moving faster than predicted, the iRobot world is still round a few more corners. Not surprisingly, the area that will succumb most heavily to the rise of the machines first is manufacturing. According to the Boston Consulting Group, they predict that robots will increase the proportion of factory tasks they perform from the current 10% to 25% by 2025.

That said, already a Chinese company Hon Hai (the world’s largest contract electronics manufacturer) is progressing with plans to replace 500,000 workers with robots in the next three years.

According to a number of studies, jobs that need human beings to perform them are rapidly diminishing. In its recent paper ‘Creativity vs Robots’, the innovation charity Nesta quotes research by academics Carl Frey and Michael Osborne, which suggests 47% of jobs are at risk of automation in just “a decade or two.”

The big question is how society will evolve and support a population which will gradually diminish in its importance to a self-sustaining eco system? Will we see queues of human beings alongside drones at the job centre? Or indeed, will unemployment figures actually become irrelevant with nation states measured positively by an upward trend alongside the usual economic parameters?

Who knows…but at least for the time being, I’ve still got a job to do.

 

“People Analytics” – Can robots replace the recruiters?

Posted on : 28-07-2014 | By : john.vincent | In : Innovation

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The recruitment industry has been largely unchanged for many years. Technology has, of course, changed the way that companies and individuals interact in the process, from online job and candidate postings with companies like Jobserve and Monster, company recruitment portals to engage with and measure preferred suppliers and online screening of candidates prior to onboarding.

However, we are now at a point where technology can really disrupt the industry through the use of Big Data. The ability to not only hire, but equally as important, retain better talent through the use of what is being called “people analytics” is now a reality. By mining the huge amounts of data that potential candidates leave, either willingly or otherwise, in their daily digital lives is allowing companies to assess the value of existing and future employees.

We won’t get into the whole privacy thing…that’s for another day.

According to Prof Peter Capelli at the Centre for Human Resources at Wharton, big data can predict successful hires better than a companies HR department.

While HR researchers have been kicking around small and simple sets of data, much of it collected decades ago, the big-data people have fresh information on hundreds of thousands of people — in some cases, millions of people — and the information includes all kinds of performance measures, attributes of the individual employers, their experience and so forth. There are a lot of new things to look at.

Now, I’m sure there are a lot of HR professionals who would argue with this! However, like all industries where technology advancements have enabled new business practices and efficiencies, recruitment is no different.

Let’s look at the evolution in one specific area, recruitment of technology professionals themselves. During the technology boom years, agencies specialising in finding talent for companies sprung up at a fast pace, armed with a collection of job board subscriptions and expense account. The game was simple….it was all about speed. How quickly could a CV hit the desk of a hiring manager.

When demand outstripped supply the question of selecting the absolute best fit candidate could often be secondary. Get someone quick…in fact, if they’ve only got 50% of the role requirements then get two!… Demand was high, margins were high and everybody was happy.

Things have changed dramatically since 2008. As demand tailed off so did margins for recruitment firms, with in-house managed services firms putting the final nail in for many new entrants.

So, now with “people analytics” in full swing, are we entering a phase where the recruitment industry will fade away completely. Of course not. For certain roles, or levels of seniority, human interaction throughout the whole process from role requirements, through search and selection is a necessity.

However, for some roles such as developers, software engineers or analysts, the use of algorithms rather than traditional routes can uncover a whole new talent pool, through techniques such as actually mining open source code. According to Dr Vivienne Ming of Gild, a specialist tech recruiter;

There are about 100 times as many qualified but un-credentialed candidates out there, at every level of ability. Organizations are creating their own blind spots, which leads to companies paying too much for their hires and to talent being squandered

Indeed, when the University of Minnesota analysed 17 studies evaluating job applicants, they actually found that human decisions were outperformed by a simple equation by at least 25%.

So, the days of the CV may be numbered. Smart companies are not waiting to advertise a role and harvest applications through their traditional channels, but are more sourcing candidates directly by casting the net into the social media waters, looking at blogs and the like. A recent survey showed that some 44% of companies looked at these platforms before hiring and candidates are now much more aware of their social media brand.

The use of people analytics continues post hire to further develop, nurture and retain talent. An example of this is actually in the world of recruitment itself where Social Talent has developed a data tool which it is testing on 2000 individuals. By analysing their daily activity, from emails, phone calls, browsing, candidate key word searching etc… it is able to build a profile of the most successful techniques and provide constructive advice through popup messages in real time.

So where does that leave the recruiters on both sides of the fence? Well, some of the smart providers are developing their own platforms to provide their customers with advanced people analytics whilst on the client side, we see the focus shifting to a smaller subset of organisational roles.

As for the traditional HR role in the talent process, we’ll leave the last word to Peter Capelli;

My bet is that the CIO offices in most big companies will soon start using all the data they have (which is virtually everything) to build models of different aspects of employee performance, because that’s where the costs are in companies and it’s also the unexamined turf in business