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HR's full of Colourful Sense Data for Machine Learning

My Doctoral Research identified statistically significant correlations of moderate strength for success in adulthood with Sensemaking and Attachment from childhood.  The Talent Development we undertake needs a shake up, and machine learning is evolutionary in the application of an increased understanding of success. Chantelle Brandt Larsen

My Doctoral Research identified statistically significant correlations of moderate strength for success in adulthood with Sensemaking and Attachment from childhood.  The Talent Development we undertake needs a shake up, and machine learning is evolutionary in the application of an increased understanding of success. Chantelle Brandt Larsen

HR is the area that is full of data for the senses. Humans are effective in organizations due to their sensemaking and attachment. 

Founding theories of sense making (Piaget) and attachment (Bowlby, Ainsworth) in my research showed statistically significant correlations to success in adulthood.

Sensemaking in organizations is how we make sense of the Organisation, business problems, opportunities and the wider macro environment. This is from the stories you here, the symbols you see visuals, offices or role models, the smells and even tastes all five senses.

Attachment is how we relate and connect to others which optimizes a persons success and their organizations.  In childhood that's the attachment with parents, as we grow that moves to friends, teachers, mentors, partners and when we enter the adult work world colleagues.

When you apply this depth of understanding to variables that can be used in talent and learning interventions in machine learning, it has enormous potential.  The supervised and unsupervised learning can have an increased chance of success to develop and evolve in the things that matter.  This has been shown in the development of a child to an adult, and what is critical to their success.  Think learning the traditional learning taxonomies are knowledge, skills and behaviour.  However, the success of talent is the ability to deal with the unknown, figure out solutions to knew problems and form new learning pathways - that's sense making.  As well as the ability to increase the size of the learning and it's impact with a super network - that's attachment.

That right now is my focus.  I am testing hypothesis and the mathematical calculation of theta and the exponential cost function.  This is identifying patterns in what makes the difference, and  machine learning that  connects learners to personalised offers.  Going further in the future machine learning is not just one sense, but also for example visual data (here mathlab is great).

What does this mean for machine learning. Well if you go back to the very first example of machine learning when Arthur Samuel in 1959 battled a computer against itself in chequers it learnt from wins and loses. 

The people data that is in our HRIS, ERP, HCM however we want to term it is rich with wins and losses, and remember failure is part of the path of learning how to be successful. Examples of the data (typically I am hypothesising this data as 'Y' with a number of variables):

  • Performance data
  • Potential data  
  • Successful hiring data
  • Leaving Data
  • Promotion Data
  • Moving Data
  • Size Network data

It is important to understand the independent variables. Unassisted learning is useful to classify and look for patterns in the data.

For example, traditionally you would design job roles, a catalogue and competencies.

In an AI environment you could understand what skills are high in certain roles, in a group of a certain performance, potential and geographic region. The data starts to then learn and can then be programmed to unassisted learning to form and be more agile to what an Organisation and person needs.

Machine sense learning in HR is an area ripe for development.

It does require some precursors:

  • data architecture and readiness
  • a cultural shift to responsive design and transformation
  • the right talent to shift to data science and machine learning

There is a sixth sense missing. In humans we call it the 3rd eye. That instinct, knowing what is right or wrong and emotion is not even there in the Business to Consumer Artificial Intelligence. So AI sensemaking is there to empower the heart and consciousness of the Organisation 'People.' 

HR Innovation Failure. Who Forgot About the Documents!

Whilst the effectiveness of the process and user interface of the new Human Capital Management (HCM) Systems are impressive there is one area in HR that has been forgotten, and there is little we can do to get away from it.  One area I am always busy working on and improving is documentation!

The documentation in HR is kind of insane!  There are the: offer letters, contracts, employee data changes where legal documents are required, leavers documentation etc.  Each document requires data collection of both what is global and local data.  Data that needs to be collected and stored in the Global HR system, and data that is only needed for local systems e.g. for payroll or legal requirements.

Just take Russia where you have for example a Global Workday, but also C1 there are circa 26 additional local data fields to collect for a New Hire to become and employee.

The HCM systems that are being implemented have pros and cons in regards of their ability to deal with global and local data. However, none resolve the documentation challenge.  There are two contenders HotDocs and Escriba that integrate well with both SuccessFactors and Workday and resolve the following problem:

  1. Data reading from systems such as e.g. Taleo, SuccessFactors or Workday
  2. Collection of global and local data if outside of the system e.g. in recruitment
  3. Data validation to reduce down stream errors e.g. special characters
  4. Automate generation of a compliant, consistent and correct document 
  5. Effective dissemination for approval
  6. Effective retrieval of the document via electronic signature
  7. Write capability of taking the data collected to the HCM

When you consider the process, also consider the documents.  This will be an area of experience and effectiveness that can be greatly improved and more innovation is to come in the future to change the face of HR ;).

 

 

 

4 Digital Profiles - Do You Recognise Them and Where Do You Want To Be?

 

Capgemini's research with MIT identified four different types of digital profile.

  1. Digirati
  2. Fashionista
  3. Beginners
  4. Conservatives

The four types of profile, have different appetites for digital technology, and a different alignment to the business strategy and goals.  Working with clients I see this in daily life where there is just not the appetite to leverage technology and transform.   The digital transformation may make strategic sense, but due to a conservative mindset, politics or silo's the business case is ultimately impacted.

Capgemini's digital research with MIT is useful is to use.   It helps companies to understand where they themselves, and where they want to be, and in quantitative terms play back the financial research on revenue and margin.

  1. Digirati's adopt technologies that align to the business goals.  Research on this group  showed:
    • Companies with a stronger digital intensity had 9% higher revenue 
    • Companies with strong transformation management 26% higher profits
  2. Fashionista strong on digital, but weak on transformation and alignment to the business:
    • Companies with a stronger digital intensity had 6% higher revenue 
    • Companies with lower transformation management -11% profit
  3. Beginners have an appetite for digital, but organisation silo's and legacy systems make it hard to make a transformational impact on the business:
    • Companies with some digital intensity had -4% revenue 
    • Companies with lower transformation management -24% profit
  4. Conservatives no to low appetite for digital, or have significant bureaucracy that impacts digital transformation:
    • Companies with a lower digital intensity had -10% revenue 
    • Companies with lower transformation management 9% higher profit

The research provides insight of barriers, and what needs to be addressed in digital transformation.  The transformation journey in a insurance company may for example be different, in order to gain buy in of an organisation entity, and adoption. A different approach would be appropriate for a Digirati in the hospitality or tech industry.

Digital and Transformation go together and this insight provides insight, SO WHAT:

  • Which are you?
  • Where do you want to be?
  • What is the right approach for adoption?

Calling BS on Ulrich

Ulrich himself has criticised his Target Operating Model in an outsourced environment, but increasingly the implementation of next generation cloud Human Capital Management Systems are coming unstuck in organisations once implemented.  I have just spent the run up to Christmas with 4 organisations who have made the same oversight.

The four roles:

  1. Strategic Partner
  2. Change Agent
  3. Employee Champion
  4. Administrative Partner

changes the depth and type of roles fulfilled by the different players, arguably there are new roles that I will cover in another blog in the future..

  • HR Business Partner
  • Centre of Expertise
  • HR Operations
  • Shared Services
  • Manager 
  • Employee

The manager and employee previously did administration and the process was often instigated and facilitated by HR.  The automation of the process provides a business case in the reduction of HR's cost to serve, but the balance shifts to the manager with a increase role to play in the instigation and facilitation of HR processes in Workday and SuccessFactors.

The challenge is whilst people management is the role of a manager; HR isn't.  In reality what I am seeing on the market is organisations where:

  • Managers are stuck but they do not know because HR is not their skill set
  • A large amount of pending transactions where managers, employees and other customers are stuck

This can be fixed if the Target Operating Model is designed end to end, with what can pragmatically implemented.  Again not consultancy BS, but working with organisations or people with experience of running operations and service.

The HCM systems do not come with the help and support for the manager because they are the User Interfaces (UI) that we expect in our private life, but those UI's also come with digital interaction to support us.  

The managers are now able to initiate HR processes, but what they need is well-defined points of contact, and the means to resolve where they have a problem are critical to core HR to be effective and efficient.

What's needed is the well designed Human Interaction Interface the next generation digital contact to support and facilitate the deeper administration role the managers play:

  • Global and Local requirements collected in plain English, validated and then automated 
  • An employee segmented service that provides the right touch support for that segment and the transaction just as in Business to Consumer markets across omni channels
  • A virtual agent that knows when support is needed with agile content like you would find in Square Space of Apple
  • The ability to speak to a human being and or book an appointment as you do at the Apple genius bar
  • Pro active campaigns from HR to improve the people impact on the business

In implementing HCM systems we must not under estimate the fundamental shift we place on managers, and the managers job is not HR.

 

 

The Robots - Like The Boyfriend Who Doesn't Quite Cut it as Marriage Material

Typically in the Enterprise Innovation I work with two types of Robots 

Two types of robots #structured and #unstructured - I would marry neither ;)

Two types of robots #structured and #unstructured - I would marry neither ;)

 

1. Robots that a simple and only do and see exactly what I tell or show them.  Structured to structured data.

2. Robots that can learn and adapt, so I can show them something but they might just take 4 or 5 times to learn how to do the job. Unstructured to Structured Data.

Frankly, way back when I was a teenager I would accept that kind of man because well, you felt just being with someone was better than being alone, and you did not know any different.  In reality you wanted a partner who would grow with you and make you stronger, and in essence needed to be a bit more clever.  

In robotics, we are not quiet there yet, however, in the the business process world I wanted to use that analogy so we understood the big strides that are coming.

Levels 0, 1, 2 and 3

0. Level 0: Don't speed up a bad or ineffective process Eliminate and Optimise first

First before we even get to robotics, actually it is the last resort!

  • If we can eliminate wasteful processes and unnecessary tasks then we should do so.  We may even be able to optimise and automate what we already have.  The amount of systems I have seen where clients are not even leveraging the true potential is fascinating, and of course then we help them.
  • In HR even SuccessFactors and Workday require Organisation Change Management (OCM).  To leverage the connected power of Human Capital Management (HCM) systems, the content and integration needs to be there.  For example, if the manager wants to click on a potential person he or she can contact for a project or succession, then there needs to be integration with the global directory and telecoms infrastructure and in a global company there may be more than one provide.

Second example, if true power of the people is to be developed and unleashed then the following dimensions need to be part of the change, but are often underestimated or just technology led:

  • Performance definition
  • Potential definition
  • Job families
  • Goals
  • Competencies mapped to their dependencies e.g. job families
  • Learning content mapped to their dependencies e.g. goals, job families and competencies
  • Experience and exposure channels enabled to include mentoring and coaching across High Potentials

1. Level 1:  Structure to Structure data (The guy perhaps I Stayed friends with but I was never going to marry)

In HRO I am often looking at uipath robots to take structured data from an online form into the HCM system where the full suite for Success Factors or Workday is not applied, there is a local process outside the legal requirements or administration of tasks such as training administration.  Here again there may be an opportunity to leverage automation first e.g.:

  • I look at SAP SuccessFactors extensions as if it were my apple developer account, and look at if it makes business sense to automate that process, and applicability perhaps on a wider scale.
  • I look at integrations of automation in processes that take significant effort and have high volume and effort, but also localisation e.g. Time and Attendance with Kronos and Workforce.
  • I look at strategic importance of the employees, like contingent workers, which is an increasing footprint of employment, with app extensions like 'Enterprise Jungle.'
  • The good thing about SAP SuccessFactors is that by Q4 2017 it will have mapped 80 local country requirements in HR.  That enables the ability to standardise across large global organisations.

2. Level 2. Unstructured Data (The guy I thought was great, but not really as he never really grew me)

This kind of robot fulfils further needs.  So for example in a HR context:

  1. Complex terms and conditions that mean in a large organisation there are multiple formats.  This robot can sort and categorise data to make efficiency gains at the top end of the process, and speed up down stream processes later on.
  2. Invoices that are in multiple formats.  HR often handles a lot of vendors due to the invoices related to people.  It looks to understand the data and learn from it's mistakes

3. Level 3: Interpret, Dialogue, Probe, Make Decisions and Apply Intelligence (The guy I ended up marrying)

This kind of robot I have not seen in the HRO space yet.  We are making advances in Artificial Intelligence, chat bots, block chain, we chat (huge in APAC and already looking at in my uni project) and ITTT (If This Then That).  In my doctorate I have been experimenting with ITTT (If This Then That) technology in the Business to Consumer Space and applying it straight to an automation logic, but in the HR space this is where I am feeding my thinking through to new projects.  Currently, I am working on to 'Re Imagine HR.'

I am blessed to work for a truly innovative company that is pushing the boundaries and bringing innovation from the Business to Consumer and Business to Business arena to Business to Employees.

If anyone has experience and or exposure to their development into the third phase I would be excited to hear more.

 

 

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