Inspiring your Team

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Start with listening, not a playbook

Early in his career, Dileep admits his primary approach was to “push” change to people from day one. Now, he begins by listening and collecting data: surveys such as “If you were me, what would you change?”, “What’s working?” and “What isn’t?” help him assess readiness and the emotional state of the organisation along the change curve.​

• Before committing to a roadmap, gather structured input from multiple levels – executives, managers and frontline teams to understand where they sit on the curve (denial, anger, confusion, crisis, acceptance).​

• Do not assume people are ready because the steering committee is enthusiastic. Measure readiness explicitly, then tailor pace and messaging to where people actually are, not where the plan says they should be.

Programme failure is often emotional, not technical

Dileep highlights several recurring reasons programmes fail, and most of them are human, not technical.​

Common failure patterns:

• Fear of failure shuts down communication – when teams are scared of missing deadlines or targets, they stop raising risks early, which increases the probability of unwanted surprises later.​

• Everyone speaks a different language – engineers talk frameworks, architects talk patterns, executives talk outcomes, and clients feel they asked for a “red car” but often end up with a “gold car.”​

• Over‑indexing on process over people – risk logs, governance and tooling (for example, Jira) are in place, but no one is checking whether people genuinely understand the goal or feel safe to share problems.​

Practical lessons:

• Make psychological safety a governance concern: explicitly reward early risk‑raising and treat missed assumptions as learning, not blame.​

• Force translation into plain language: ask for analogies and non‑technical explanations in key forums to ensure stakeholders genuinely understand what is being proposed and built.

From intuition to data‑driven change

A major evolution in Dileep’s leadership is a shift from mostly qualitative judgement to strong data‑driven decision making. Boards and C‑suites are time‑poor, and simple metrics used to drive critical decisions promptly.​

• Treat every major change like a product: define clear success metrics up front (value, adoption, satisfaction, risk) and instrument your programme so you see movement over time, not just delivery milestones.​

• Use both lead indicators (surveys, sentiment, adoption patterns) and lag indicators (revenue, cost, cycle time) to know when to pivot, pause or stop; use data to challenge sunk‑cost bias.​

• If you cannot explain the performance of your initiative with a small set of meaningful numbers, you will struggle to keep senior sponsors engaged, especially in an AI‑accelerated world where alternatives are emerging constantly.​

Leading individuals, not roles

Dileep is explicit that leadership starts with knowing “the person behind the title.” He pays close attention to life context, energy levels and aspirations to decide when to stretch someone, when to protect them, and when to help them redefine their path.​

Key points for leaders:

• Use structured career frameworks so people can see where they are, where they can go next and what capabilities they need to build – and then align real work to those paths.​

• Have honest conversations about performance and growth: praise specifically when work is good, and equally clearly explain when it is not, focusing on the “why” and how to improve.​

In a world where AI can generate code and content quickly, your differentiator as a leader is your ability to grow people’s thinking and judgement, not just assign tasks.​

AI as an enabler, not an enemy

Dileep compares AI to “half‑time oranges” in football/soccer: something that gives you a boost rather than something that plays the game for you. He encourages technologists to identify where AI can elevate their work and where human strengths like judgment, empathy and complex problem solving need to be amplified.​

• Help teams use AI to speed up lower‑value work (research, drafting, options generation) so they can spend more time on stakeholder alignment, creative problem solving and decision‑making.​

• Reassure teams that roles will change, but problem‑solvers and systems thinkers will remain in high demand; focus development on these capabilities.​

Practical lesson:
Encourage your teams to experiment with AI on real programme tasks, but always pair AI output with human reflection and context – “What is this tool missing that only we can see from our customers and culture?”​

The daily habit that compounds

Learn one new thing every day and regularly do something that stretches or scares you. Admit when you don’t understand a term.

• Ask three people at different levels of your current programme: “If you were me, what would you change first?” and listen carefully to what you hear.​

• Identify one decision where you are currently “going with your gut” and define two or three data points you could gather in the next month to validate or challenge that instinct.​

• Amit when you don’t understand a term.

• Learn one new thing every day and regularly do something that stretches or scares you.