Maximizing OKR Success with AI: Enhancing Goal-Setting, Tracking, and Execution without Losing the Human Touch

CXOToday has engaged in an exclusive interview with Deepa Nagarajan, Founder and CEO, DEEPA NAGARAJAN LLP

How can AI enhance the setting and tracking of OKRs in organizations?

This is a trend in that every area of business is impacted or perceived to be impacted by the penetration of AI or AI enablement.  I very strongly believe that AI will significantly enhance the quality of OKR implementation.  It is a matter of WHERE you use AI.  Most OKR tools integrate generative AI to help craft OKRs.  While I think this can help understand OKRs better, I would caution organizations against relying too much in gen AI to define the OKRs.  You’ll spawn a workforce which does not understand the OKR philosophy and become dependent on AI to do their job without understanding how the business works or how they are contributing to the growth of the organization.

But Ai does have its use.  AI can help generate meaningful reports and give predictive insights on where the execution gaps are and what we can do about it.  Remember – using the power of AI to craft your OKRs will not help you tame the devil of execution.

What role can machine learning (ML) algorithms play in predicting OKR outcomes, identifying potential roadblocks, or suggesting adjustments to OKRs?

In the ever-advancing world of AI, the ML systems learn better with large amounts of data.  And every single OKR implementation in each organization produces a vast amount of business data which can be used to make better decisions and define better OKRs in the subsequent cycles.  Even though OKRs are not a new-age phenomenon, what data is fed into the machines to trigger the learning, and the very quality of this data is very important.  If done right, it can be a very powerful tool to help organizations to make course corrections, get better business visibility, and reduce the gap between ambitions and outcomes.  One key point to bear in mind is that the machine learning models can be quite complex in their interpretations and there may be a lack of transparency in how the decisions are arrived at.  It may take a while for the maturity to set in.  Nevertheless, the benefits outweigh the rock of caution, if you can learn to flow around those rocks and derive the maximum benefit out of ML algorithms.

How can natural language processing (NLP) be leveraged to facilitate more effective OKR goal-setting, tracking, and feedback?

NLP, which is a subfield of Deep Learning can help focus on the interplay between machines and natural way of speaking a human language.  This enables machines to understand, interpret, and generate output from natural way of a human’s speech, in a way that is both meaningful and useful.  If NLP were to be incorporated well in OKRs, it could help translate a young employee’s excited statement like “Let’s create a kickass customer experience for our online buyers” into s specific Key Result like “Improve customer NPS Score from the current 3.5 to 4.5 by end of Q2.”

The same bridging and rejigging can be applied while sharing a better and actionable feedback with team members.

What are some potential benefits and drawbacks of using AI-driven OKR systems, and how can organizations strike a balance between technology-enabled efficiency and human judgment?

One thing is for certain – technology was and is an enabler.  The current OKR tools are very rudimentary in their adoption of AI and we have a long way to go to be able to use AI effectively for OKR Management.  Any system runs on the principle of GIGO (Garbage In, Garbage Out).  So, the ability to use and leverage AI-based systems will depend on the concentricity of the organization’s purpose and its execution efficiency.

Can AI help address common OKR challenges like goal alignment, progress tracking, and employee engagement? If so, how?

AI is not (yet) a self-aligning system.  Which means while the data generated by AI tools can help point the larger issues, the responsibility of the intuitive, and right-brained decision making will largely lie within the human’s realm.  In the area of progress tracking AI can help significantly through backend calculations, analytics etc.

We are designing an AI based growth management tool that helps companies not just define and track their goals but do it with the RIGHT syntax and foundational principles of OKRs.  It also helps to see your journey from goals to growth.

Just like any language in the world, OKR has a specific structure and style to follow – the OKR Syntax.  And this is where our growth management tool, Calyber, will stand high amidst the spawn of tools that we see in the market.

What makes your TRICEA© methodology effective in implementing OKRs, enabling successful outcomes for diverse companies and across industries? 

When it comes to OKRs, people jump straight into defining Objectives and key results without even understanding that it is not about just setting some goals.  It is an organizational transformation initiative and if you are not ready for the change it brings to your way of working, you might not extract the full benefit of OKRs or worse, you may fail.  Just for the record, the OKRs success rates are as abysmal as the startup success rates.  And it is not better in SMEs or larger organizations which may even have inflexible systems and processes already in place.  With such small rate of success, we had to find a way to understand the underlying reasons and help fix them.  One of the many decisions we made is to start treating OKRs as a culture management tool and growth management model.  This paradigm shift in the vision is the genesis of our 100% successful OKR Implementation model TRICEA.

TRICEA is an acronym for Tracked/Tabulated, Reviewed/Rectified, Integrated, Collaborated/Celebrated, Engaging, Aligned.  This method was developed by my organization after several years of OKR implementations across industries, geographies, and sizes of companies.  The model is flexible to fit snugly with your unique needs and company culture.  And yet standardized enough to help you make it a seamless process inside your organization.  It is a step-by-step approach to implement OKRs covering all aspects from pre-assessments to disciplines of execution and also closing the loop with the 3DM Process (Data Driven Decision Making).