Machine Human collaboration path starts with defining guidelines

Humans are in the driving seat, so get to decide the rules of the collaboration setting. However, as the arrangement evolves, machines may also start taking autonomous execution and restricts flexibility.  

   

Overarching principles and design guidelines 

1. At all times, HR has to be aligned with business goals and organisational stated values.  Talent is a key strategic asset, and its acquisition, growth, deployment for business goals is the core non-negotiable accountability.
2. Building a positive work environment, with shred sense of equity and fairness to maximize productivity and satisfaction remains core.  
3. Accountability towards Legal, ethical, and policy compliance across geographies, especially in multi-sector environments, is non-negotiable.
4. All decisions recommended by Machines (AI) should be explainable and may require human review — especially in critical or ethical contexts. 
5. There should be Intelligence-Led Decisioning ie decisions to be informed by predictive insights, prescriptive analytics, and scenario modeling provided by machines.
6. Agent-Led Execution of the repetitive and logic-based tasks. There is openness to redefine the present processes, workflows and decision rights to make tasks amenable to agent led delivery.  
7. Continually strive towards hyper-personalisation, based on profile, experience, interest, intent, and opportunity capture
8. High standards of Digital Ethics and Transparency supported by Clearly define data boundaries, model transparency, and ethical standards for use of employee data and AI-led decisions
9. Modular & Platform-Based Architecture, allowing for easy integrations with other systems and introduce agents. 
10. Reimagination and experimentation approach supported by feedback loops to continue evolving and moving on the evolution trajectory
11. Pace and realm of transition to accommodate employee's adaption challenges, keeping intact trust while managing negative associations like privacy concerns, algorithimic bias or over de-humanisation. 
12. There is always human escalation path available for any automated processes.      

Translating these principles and guidelines into action would require setting up new institutional structures like joint ethics and governance committees and cross functional teams, enhanced role of CHRO, CDOs and other leaders.  

Besides, this would require reimagining of the role of HR workforce as they share their work with machines going forward.       

Handing over to Machines : The Why and why-not Question?

Like all dimensions of work, the conventional work done by Human resource professional is also under scanner and expected to be given to, fully or partially, to machines.  

The prime motivation is to leverage the tireless energy, unbiased application of decision rules, immense retrieval and computing capabilities and NLP based interactions of new set of digital technologies (RPA, AI ML, Chatbot, Agentic-AI) for the good of employee, managers and organisation.  

The Why-Machine question?

The key motives for introducing machine power in HR context hovers around the following:

1 If Talent is the strategic asset, then machines help identify, acquire and deploy this asset better, and more efficiently. It can provide fitment score. predict the performance outcome, attrition risk and often provide the hidden talent option that is hidden in the remote work location.    

2 If employee experience at workplace is to be as good and personalised as at market-place, we can emulate same solutions for validation, interaction, recommendations and transactions, chatbots for example.    

3 If trust, transparency and auditability behind routine transactions are important, machines deliver better and at scale, using RPA as a disciplined agent.   

4 If machine releases cognitive capacity of the workforce, by taking over routine and rule-based decisions, why not? And machine capacity to adjust to scale is far more than of workforce. 

5  If the outfall of mistake by machine is manageable and not disproportionate from ethical, reputational and economics consideration, lets go ahead.   

In recognition of the above, over 70% big corporations are using machines in HR for some purpose or other.  

The Why-Human question?

At the same-time, need for putting Human in the loop is often felt: 

1 If the decision or action would create negative consequence, (say disciplinary action, dismissal), human judgement is warranted?

2 If there is less confidence in defending explainability of decisions or actions by machines to externl party, keep Human in the loop

3 If the empathy and emotions are as important as the content of the interaction for employee satisfaction, oblige

4 If the reliability of the data sets driving transcations and decisions are a suspect, let humans decide

5 If the decisions require case-2-case considerations with high level of contextual and subjective discretion, humans are not replaceable.

Moving work from humans to machines has to be a deliberative, and structured transition, ensuring coordinated readiness around policies, processes, technology and people dimensions, to make it seamless and well recived by stakeholders.         

MBA 101 in action: Running business - the HUL way!

Sudhir avers that it took him only 4 months to type the book although it took 20 years to write. In similar vein, it does not take long for most organizations to appreciate the advantages of running business in line with management principles taught in business schools- mostly under 101 courses, but most organizations may take lifetime to practice these  principles in letter and spirit. And this is the where Hindustan Lever has got the edge.

Most of the book lessons may not be new, but how Hindustan lever implements them come live through experience and practice sharing that Sudhir has brought out very effectively. Most companies, especially operating in developing economies, profess focus on growth, cost consciousness, meritocracy, differentiated workforce strategies implemented in sensitive and humane manner, grounded leadership, and importance of balancing character and competency while defining their definition of desirable talent.

Given the richness of experience Hindustan lever managers have in FMCG space- across all 4Ps of marketing, any conclusions or suggestions coming from their side merits deliberation. Defining marketing process as understanding customer needs and solving customer problems defined in-terms of Job to be done, is powerful way to differentiate it from its components, including publicity, advertisement or sales.

Some interesting insights that are worth reflecting, to understand their relevance in one’s business context includes:
1. Buyers are far more similar in behavior than you think- avoid over-segmentation
2. What matters is the quality the consumer gets and not quality designed in the laboratory
3. It is easier to get consumers adopt new category than to get them increase consumption
4. Price discounts do not recruit new consumers, encourage existing consumers to buy more
5. Lower price point is more important than cheaper price per kilo for low-income consumers
6. Build portfolio of brands at different price points to be resilient in times of crisis
7. Sales is a cost and not a revenue centre
8. Ensure availability of stock and not depth of stock- keep stock refilling cycle short.
9. Spend more on advertising deployment and not on advertising creation.
10. Look for reach than repetition in media plan- whisper to as many

Among my favorites is the practical suggestion of ensuring that decision has both the right and left brain backing – as Sudhir mentions that decisions are often created in inebriated state and validated and firmed up in sober state.

 Book full of insights that are real contradictions that become  obvious in hindsight!