Insurance Commission of Western Australia

Leading enterprise-wide digital transformation initiatives, reporting directly to the CIO. Responsible for managing the overall IT Portfolio and overseeing strategic programs, including Office Modernisation, Data Security, Document Management and Enterprise Data Management.

● Strategic Leadership & Innovation – Spearheading workplace modernisation, IT infrastructure upgrades, and digital transformation initiatives to enhance operational efficiency.
● Portfolio Governance – Managing multiple PMs and ensuring successful program execution aligned with business objectives.
● Enterprise Data Management – Establishing robust data governance frameworks and modernising document management systems to improve accessibility and compliance.
● Stakeholder Engagement – Collaborating with C-level executives and presenting transformation roadmaps to the board.

Portfolio Director

NRI Australia & New Zealand

● Directed a $30 M Enterprise Data-Management program, cutting data duplication by 35% and raising data-trust scores to 96%. 
● Achieved 100% Essential-8 cyber compliance, reducing high-risk vulnerabilities by 30%. 
● Built a Program & Project Management Community of Practice (100 + members) that trimmed project start-up time 30%.
● Mentored 15 junior PMs, seven promoted within 12 months, and improved stakeholder-satisfaction scores by 40%.

Practice Lead - Program and Project Management

Standard Chartered Bank

Led multi-million-dollar transformation programs across finance, compliance, and DevOps, delivering efficiency improvements and regulatory compliance.

● Regulatory Reporting Transformation – Improved reporting accuracy by 25% across 15 countries, ensuring regulatory alignment.
● Data Platform Transformation ($15M Program) – Standardized financial data across 25 applications, reducing reconciliation issues by 30% and enhancing compliance.
● Cost-Saving Initiatives – Identified and implemented process optimizations, achieving $750K in savings and reducing time to market by 40%.
● DevOps & CI/CD Implementation – Increased deployment frequency by 300%, delivering $680K in cost savings.

Program Manager

Great Eastern Life

●	Executed a data lake project integrating 20 diverse source systems and 10 TB of structured, unstructured, and semi-structured data, including real-time ingestion. 
●	Increased operational efficiency by 25%, reduced data analysis time by 30%, and enabled data-driven decisions 50% faster with 15% greater accuracy, enhancing overall business success and performance.
●	Managed technical project plans and timelines, established data flow pipelines and governance frameworks, developed a scalable ETL framework for the data lake, and implemented handshake mechanisms for daily feeds.
●	Led project initiatives by providing required oversight, task assignment, and guidance to a globally sourced development team, resulting in a cost savings of $110,000 and project completion 3 months early by using the best project management practices.
●	Developed and implemented the Target Operating Model (TOM) for the application and helped in the establishment of the production support team.

Assistant Vice President Technical Delivery Manager

Tata Consultancy Services

●	As a Project manager, planned, implemented, and executed data projects, reducing compliance risk and improving reporting accuracy by 20%.
●	Managed an offshore team and provided timely guidance, task assignment, and project delivery, increasing productivity by 15%.
●	Collaborated with Group Treasury users and business analysts to gather requirements, understand data flow, and develop a feasible and efficient design that fits seamlessly into the existing framework, reducing implementation time by 25%.
●	Chaired the design and infrastructure working group, concentrating on project architecture and infrastructure requirements, streamlining data and control flow diagrams, resulting in a 20% improvement in workflow efficiency.
●	Optimized technical implementation of the proposed architecture, achieving a 10% reduction in infrastructure costs.

Assistant Consultant Delivery Lead

HCL Technologies

●	Worked as the ETL lead for on-site ETL team, managing a team of 15 ETL developers in Singapore.
●	Involved in the requirement gathering and feasibility analysis process of the project.
●	Interacted with the BAs in order to prepare and finalize the Functional Specs for different sources system and countries.
●	Designed Low Level Design Document for the Project.
●	Involved in forming the DataStage Coding standards, DS Objects naming convention standards, DS Category/ Unix Folder Creation standards and DataStage Code Review checklist. 
●	Working as the single point of contact for all client interaction for Post ODS component of the project.
●	Interacting with the business team for taking the requirement and for the timely closure of SIT/UAT. Ensuring that patches for issues during SIT/UAT are released on time.

Senior Software Engineer Technical Lead

Aon Hewitt

●	Involved in feasibility analysis for the implementation of the project (Mainframe system to the DataStage PX Version) due to the complex process.
●	Analyzed, designed and created the DataStage implementation plan for the Voyager Module.
●	Designed and prepared low level technical design document for Voyager Module.
●	Involved in handling training, doubt clearing sessions and performance tuning sessions for 15 member project team.
●	Responsible for creating DataStage Coding standards, DS Objects naming convention standards, DS Category/ Unix Folder Creation standards and DataStage Code Review checklist. These standards were implemented in all ETL jobs.
●	Involved in direct interaction with the client for providing technical solutions to the problem being faced for the optimized running of jobs.
●	Involved in performance tuning of jobs. Provided no of solution like increase of ulimit, increase of the scratch space.

Informatica Developer

Syntel

●	Involved in creating Data Stage jobs for DW Dimensions and implemented Slowly Changing    Dimension (SCD, Type 2)
●	Integrated the entire Performance Application through Data Stage Sequencer and scheduled accordingly.
●	Prepared specifications, Unit Test plans, and test cases for the Data warehouse related jobs.
Involved in Analysis, Designing, Coding and Unit Testing of the ETL related jobs.

DataStage Analyst Programmer

I transform fragmented systems and siloed data into AI-ready, board-aligned ecosystems.

Over 20 years, I’ve steered $70 M digital, data & AI portfolios, cutting data duplication 35 % and freeing multi-million-dollar run-cost savings, launching 3 revenue-generating AI products, and accelerating regulatory reporting 40 % through purpose-built governance frameworks.

Partnering directly with CIOs, CDOs and Boards, I provide strategic clarity, disciplined execution and stakeholder alignment. 

I turn around stalled modernisation programs, embed portfolio controls, and lead cross-functional teams under high-stakes conditions across government, financial services and insurance sectors.

Current focus: aligning AI governance with enterprise risk appetite so innovation scales without compromising compliance or public trust.

Focus areas:
 • Digital & Data Portfolio Leadership (up to $70 M)
 • AI Program & Product Delivery
 • Enterprise Data Governance & Risk
 • C-Suite & Board Communication
 • Regulatory & Compliance Transformation

Open to APAC-regional or US-remote roles where strategic delivery, product leadership and enterprise modernisation intersect, let’s connect.

𝟑-𝐋𝐚𝐲𝐞𝐫 𝐈𝐧𝐟𝐥𝐮𝐞𝐧𝐜𝐞 𝐌𝐚𝐩: 𝐰𝐡𝐨 𝐬𝐢𝐠𝐧𝐬, 𝐰𝐡𝐨 𝐬𝐡𝐚𝐩𝐞𝐬, 𝐰𝐡𝐨 𝐜𝐨𝐧𝐯𝐢𝐧𝐜𝐞𝐬

6 signatures vs 1 nudge. That is the cost of ignoring influence.
Decisions are shaped before the meeting starts. 
Slide packs fail when we map roles, not power.

𝐌𝐚𝐩 𝐭𝐡𝐞 𝐭𝐡𝐫𝐞𝐞 𝐥𝐚𝐲𝐞𝐫𝐬:

→ 𝐅𝐨𝐫𝐦𝐚𝐥: 
Titles, budget, duty; the official owner, approver, risk gate.

→ 𝐒𝐡𝐚𝐝𝐨𝐰: 
Side agreements, vendor sway, cross-portfolio trade that moves outcomes.

→ 𝐈𝐧𝐟𝐨𝐫𝐦𝐚𝐥: 
Trust paths, timing, and the person who gets called after the meeting.

𝐁𝐮𝐢𝐥𝐝 𝐢𝐭 𝐭𝐡𝐢𝐬 𝐰𝐞𝐞𝐤
→ Tag stance with simple RAG.
→ Note each actor’s currency: influence, access, expertise.
→ Validate with short pulses, not long workshops.
→ Keep it live for each decision, not as a shelf artefact.

𝐖𝐨𝐫𝐤 𝐚𝐥𝐥 𝐭𝐡𝐫𝐞𝐞 𝐥𝐚𝐲𝐞𝐫𝐬 𝐨𝐧 𝐨𝐧𝐞 𝐩𝐚𝐠𝐞 𝐚𝐧𝐝 𝐲𝐨𝐮 𝐬𝐭𝐨𝐩 𝐠𝐮𝐞𝐬𝐬𝐢𝐧𝐠. 
Decisions move faster because you brief the real deciders before the room.

P.S. Have you seen an unexpected influencer change a board outcome? 
P.S.S. What did it teach you?

#BoardroomInfluence #Programleadership #Governance #Decisionmaking #Strategy

Punardeep Singh

Portfolio Director • $70M AI, Data & Digital Portfolio • AI Product & Program Leadership • Scaled Enterprise Solutions • Trusted Advisor to C-Suite & Boards

𝐑𝐮𝐧-𝐑𝐞𝐚𝐝𝐢𝐧𝐞𝐬𝐬 𝐒𝐜𝐨𝐫𝐞: 𝐂𝐥𝐚𝐫𝐢𝐭𝐲 𝐁𝐞𝐟𝐨𝐫𝐞 𝐂𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞

The metrics were green, yet confidence was red. 
That contrast is what inspired the Run-Readiness Score.

𝐌𝐨𝐬𝐭 𝐩𝐚𝐢𝐧𝐟𝐮𝐥 𝐠𝐨-𝐥𝐢𝐯𝐞𝐬 𝐡𝐚𝐩𝐩𝐞𝐧 𝐰𝐡𝐞𝐧 𝐫𝐞𝐚𝐝𝐢𝐧𝐞𝐬𝐬 𝐢𝐬 𝐟𝐮𝐳𝐳𝐲, 𝐭𝐨𝐨 𝐦𝐚𝐧𝐲 𝐜𝐡𝐞𝐜𝐤𝐥𝐢𝐬𝐭𝐬, 𝐭𝐨𝐨 𝐦𝐮𝐜𝐡 𝐝𝐞𝐛𝐚𝐭𝐞 𝐚𝐧𝐝 𝐧𝐨 𝐬𝐢𝐧𝐠𝐥𝐞 𝐭𝐫𝐮𝐭𝐡.

𝐖𝐡𝐚𝐭 𝐢𝐭 𝐢𝐬:
One number before cutover that blends SLOs, rollback, and monitoring.
Green you ship. Amber you fix. Red you stop.

𝐇𝐨𝐰 𝐢𝐭’𝐬 𝐛𝐮𝐢𝐥𝐭:
𝐒𝐋𝐎 𝐫𝐞𝐚𝐝𝐢𝐧𝐞𝐬𝐬: 
→  SLOs for key user journeys. Error budgets set. Burn-rate alerts tested.

𝐑𝐨𝐥𝐥𝐛𝐚𝐜𝐤 𝐫𝐞𝐚𝐝𝐢𝐧𝐞𝐬𝐬:
→ Rollback rehearsed on a prod-like stack. 
→ Time to restore measured. 
→ Data changes are reversible or behind feature toggles.

𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 𝐫𝐞𝐚𝐝𝐢𝐧𝐞𝐬𝐬:
→ Dashboards live. Synthetic checks are in place. 
→ On-call, runbooks, and paging tested.

𝐒𝐢𝐦𝐩𝐥𝐞 𝐟𝐨𝐫𝐦𝐮𝐥𝐚:
Score = 40 % SLO + 35 % rollback + 25 % monitoring
Any critical fail caps the score at 59
Green 85 – 100 • Amber 70 – 84 • Red 0 – 69

𝐅𝐢𝐯𝐞-𝐬𝐭𝐞𝐩 𝐠𝐚𝐭𝐞, 𝐲𝐨𝐮 𝐜𝐚𝐧 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭 𝐭𝐡𝐢𝐬 𝐰𝐞𝐞𝐤:
1️⃣ List the checks in each area with clear pass/fail.
2️⃣ Assign the weights above and publish the rubric.
3️⃣ Auto-calculate the score in CI on each release candidate.
4️⃣ Enforce the gate, no cutover if the score is red or any critical check fails.
5️⃣ After go-live, review incidents and tune the weights.

𝐖𝐡𝐲 𝐢𝐭 𝐰𝐨𝐫𝐤𝐬:
• Makes risk visible at a glance
• Creates a shared language across product, engineering, and operations
• Stops hero launches and opinion fights
• Turns readiness into data, not vibes

𝐂𝐥𝐚𝐫𝐢𝐭𝐲 𝐛𝐞𝐟𝐨𝐫𝐞 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞. 𝐒𝐜𝐨𝐫𝐞 𝐢𝐭, 𝐭𝐡𝐞𝐧 𝐬𝐡𝐢𝐩.

P.S. What would you add to the Run-Readiness Score in your context? Share your must-have checks below.

Run-Readiness Score: Clarity Before Confidence

𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐒𝐭𝐫𝐞𝐬𝐬 𝐓𝐞𝐬𝐭: 𝐖𝐨𝐮𝐥𝐝 𝐲𝐨𝐮𝐫 $𝟓𝟎𝐌 𝐩𝐫𝐨𝐠𝐫𝐚𝐦 𝐬𝐮𝐫𝐯𝐢𝐯𝐞 𝐚 𝐬𝐡𝐨𝐜𝐤?

Most portfolios look strong until something breaks.
A budget freeze. A vendor exits. A new rule lands overnight.

𝐔𝐧𝐜𝐞𝐫𝐭𝐚𝐢𝐧𝐭𝐲 𝐢𝐬 𝐧𝐨𝐫𝐦𝐚𝐥. 𝐔𝐧𝐩𝐫𝐞𝐩𝐚𝐫𝐞𝐝 𝐢𝐬 𝐨𝐩𝐭𝐢𝐨𝐧𝐚𝐥.

𝐓𝐡𝐞 𝐬𝐭𝐫𝐞𝐬𝐬 𝐭𝐞𝐬𝐭 𝐢𝐧 𝟓 𝐬𝐭𝐞𝐩𝐬:

1️⃣ 𝐃𝐞𝐟𝐢𝐧𝐞 𝐭𝐡𝐫𝐞𝐞 𝐬𝐡𝐨𝐜𝐤𝐬:
 • Budget freeze at 20%
 • Vendor exit with 30 days notice
 • Regulatory surprise with a 90-day deadline

2️⃣ 𝐒𝐞𝐭 𝐬𝐮𝐫𝐯𝐢𝐯𝐚𝐥 𝐫𝐮𝐥𝐞𝐬:
 • Outcomes you must protect
 • Maximum slip you will allow
 • Cap total cost

3️⃣ 𝐅𝐢𝐧𝐝 𝐬𝐢𝐧𝐠𝐥𝐞 𝐩𝐨𝐢𝐧𝐭𝐬 𝐨𝐟 𝐟𝐚𝐢𝐥𝐮𝐫𝐞:
 • People, suppliers, systems
 • If one fails, what stops and what still ships

4️⃣ 𝐌𝐨𝐝𝐞𝐥 𝐲𝐨𝐮𝐫 𝐦𝐨𝐯𝐞𝐬:
 • Pause low-value work
 • Rescope to minimum business increments
 • Swap suppliers or add an internal squad
 • Cut features that do not move the needle

5️⃣ 𝐃𝐞𝐜𝐢𝐝𝐞 𝐟𝐚𝐬𝐭 𝐰𝐢𝐭𝐡 𝐃𝐄𝐂𝐈𝐃𝐄:
 • Define the shock and survival rules
 • Estimate impact on value, cost, time
 • Choose three moves to test now
 • Implement a two-week trial for each move
 • Decide the new plan by a fixed date
 • Explain the trade-offs to sponsors

𝐒𝐡𝐨𝐰 𝐬𝐡𝐨𝐜𝐤 𝐜𝐚𝐩𝐚𝐜𝐢𝐭𝐲 𝐭𝐨 𝐲𝐨𝐮𝐫 𝐛𝐨𝐚𝐫𝐝 (𝐨𝐧𝐞 𝐬𝐥𝐢𝐝𝐞)
• Scenario tested: budget freeze, vendor exit, regulatory surprise.
• Time to stabilise: days to get back to controlled delivery.
• Value protected: % of planned benefits you still land in 12 months.
• Runway: weeks of funding at current burn after the shock.
• Decisions in 14 days: stops to approve, swaps to approve, scope to defer.

𝐀 𝐬𝐢𝐦𝐩𝐥𝐞 𝐢𝐧𝐝𝐞𝐱 𝐲𝐨𝐮 𝐜𝐚𝐧 𝐪𝐮𝐨𝐭𝐞:
Shock capacity = value protected after shock ÷ planned value
Report the worst of the three scenarios as your headline number.

Boards do not want perfect forecasts. They want proof you can absorb hits, stay legal, and still land value.

P.S. What shock would hurt your portfolio most right now, and what is the first move you would make to absorb it?

𝐓𝐡𝐞 𝐇𝐢𝐝𝐝𝐞𝐧 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐓𝐚𝐱: 𝐰𝐡𝐞𝐧 𝐥𝐞𝐠𝐚𝐜𝐲 𝐜𝐨𝐧𝐧𝐞𝐜𝐭𝐨𝐫𝐬 𝐝𝐫𝐚𝐢𝐧 𝐦𝐢𝐥𝐥𝐢𝐨𝐧𝐬.

Most teams track project budgets. Few track integration drag. That gap is where millions leak.

Legacy connectors look cheap on paper. They are slow to change. They fail under load. They carry quiet fees.

𝐖𝐡𝐞𝐫𝐞 𝐭𝐡𝐞 𝐝𝐫𝐚𝐢𝐧 𝐡𝐢𝐝𝐞𝐬
→ Delay cycles
→ Error amplification
→ License and platform bloat

𝐀 𝐬𝐢𝐦𝐩𝐥𝐞 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 𝐭𝐨 𝐪𝐮𝐚𝐧𝐭𝐢𝐟𝐲 𝐭𝐡𝐞 𝐝𝐫𝐚𝐠:
Use the TAX score per integration per quarter.

T = Delay cost = slip days × daily burn rate × dependent teams
A = Accuracy cost = failed message rate × volume × rework minutes × loaded rate ÷ 60
X = Licensing cost = connector fees + per-endpoint charges + idle capacity
𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐓𝐀𝐗 = 𝐓 + 𝐀 + 𝐗

𝐓𝐢𝐩: Keep unit rates simple and publish assumptions so finance can verify.

𝐇𝐨𝐰 𝐭𝐨 𝐬𝐮𝐫𝐟𝐚𝐜𝐞 𝐜𝐨𝐬𝐭𝐬 𝐭𝐨 𝐛𝐨𝐚𝐫𝐝𝐬 𝐚𝐧𝐝 𝐂𝐅𝐎𝐬:
→ One-page Integration Tax Statement.
↳ Top five connectors by TAX, run-rate per quarter, and trend for the last two quarters.

→ Cost to stay vs cost to change
↳ Annual TAX vs one-off modernisation cost, payback in months.

→ Tie the risk to money
↳ Convert error rates to customer impact and service credits.

→ Make funding real
↳ Retire two high-TAX connectors to fund one modern adapter.

𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 𝐭𝐡𝐢𝐬 𝐰𝐞𝐞𝐤
𝐁𝐚𝐬𝐞𝐥𝐢𝐧𝐞: pick three critical flows and calculate TAX with real volumes.
𝐏𝐫𝐢𝐨𝐫𝐢𝐭𝐢𝐬𝐞: rank by payback months; under 12 months go first.
𝐂𝐡𝐨𝐨𝐬𝐞 𝐭𝐡𝐞 𝐩𝐚𝐭𝐡: refactor, replace, or retire.
𝐂𝐨𝐦𝐦𝐢𝐭: 90-day exit plan, owner named, milestones set, weekly TAX update.

𝐖𝐡𝐲 𝐭𝐡𝐢𝐬 𝐦𝐚𝐭𝐭𝐞𝐫𝐬
Budgets show what you spend. TAX shows what standing still costs. 
When leaders see both, they fund the right change.

P.S. What metric has helped you prove integration pain to finance or the board? Share your approach below.

#Integration #Digitaltransformation #CIO #CFO #Boardreporting #Riskmanagement

The Hidden Integration Tax

Most boards think more audits mean better governance. 
They are wrong.

Teams are not tired of controls. 
They are tired of chaos disguised as compliance.

𝐘𝐨𝐮 𝐤𝐧𝐨𝐰 𝐟𝐚𝐭𝐢𝐠𝐮𝐞 𝐢𝐬 𝐫𝐢𝐬𝐢𝐧𝐠 𝐰𝐡𝐞𝐧:
 • Audit prep takes longer than delivery.
 • Evidence is recopied because every auditor asks differently.
 • Risk meetings become paperwork sessions.
 • No one can explain what changed since the last review.

𝐒𝐡𝐢𝐟𝐭 𝐭𝐨 𝐚 𝐋𝐢𝐠𝐡𝐭𝐰𝐞𝐢𝐠𝐡𝐭 𝐀𝐮𝐝𝐢𝐭 𝐑𝐡𝐲𝐭𝐡𝐦:

• 𝐅𝐨𝐜𝐮𝐬 𝐰𝐡𝐞𝐫𝐞 𝐫𝐢𝐬𝐤 𝐢𝐬 𝐫𝐞𝐚𝐥:
Target the 20 percent of risks that drive 80 percent of impact.

• 𝐄𝐦𝐛𝐞𝐝 𝐜𝐨𝐧𝐭𝐫𝐨𝐥𝐬 𝐢𝐧 𝐝𝐚𝐢𝐥𝐲 𝐰𝐨𝐫𝐤:
Automate evidence capture and link it to operational data. Compliance happens by doing, not by proving later.


•𝐑𝐮𝐧 𝐚 𝐭𝐢𝐠𝐡𝐭 𝐜𝐚𝐝𝐞𝐧𝐜𝐞:
Hold a 30-minute weekly check on the critical controls. 
Publish a one-page card: pass, fail, waiver, expiry, named owner.

• 𝐌𝐞𝐚𝐬𝐮𝐫𝐞 𝐢𝐦𝐩𝐚𝐜𝐭, 𝐧𝐨𝐭 𝐚𝐜𝐭𝐢𝐯𝐢𝐭𝐲:
Ask, “What decision will this review inform?” 
Track risk reduction and control strength, not checklist volume.

• 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬𝐥𝐲 𝐥𝐢𝐠𝐡𝐭𝐞𝐧:
 After each cycle, remove redundant checks and update the control library.

Governance is not about proving control. 
𝐈𝐭 𝐢𝐬 𝐚𝐛𝐨𝐮𝐭 𝐜𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞.

P.S. Would your portfolio pass a one-page control health review today?

#Digitalassurance #Programleadership #Governance #Auditreadiness #Resilience #Riskmanagement

Lightweight Audit Rhythm: confidence without the fatigue

𝐁𝐮𝐢𝐥𝐝 𝐭𝐫𝐮𝐬𝐭 𝐟𝐢𝐫𝐬𝐭. 𝐓𝐡𝐞𝐧 𝐛𝐮𝐢𝐥𝐝 𝐦𝐨𝐝𝐞𝐥𝐬.

The most significant risk in your AI strategy isn’t technology failure.
It’s an ethical failure.

Most teams ask, "Can we build it?"
The best question is whether “Should we build it?”

𝐀 𝐬𝐢𝐦𝐩𝐥𝐞 "𝐏𝐑𝐈𝐌𝐄" 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 𝐭𝐡𝐚𝐭 𝐩𝐫𝐞𝐯𝐞𝐧𝐭𝐬 𝐫𝐞𝐠𝐫𝐞𝐭𝐬:

𝐏𝐮𝐫𝐩𝐨𝐬𝐞:
Say why this exists. Name the human benefit. 
If the benefit is unclear, stop.

𝐑𝐢𝐠𝐡𝐭𝐬:
Get informed, specific consent. 
Use only the data you need. Give people control.

𝐈𝐦𝐩𝐚𝐜𝐭:
Who benefits. Who could be harmed? 
Test for bias. Make it fair, safe, and explainable.

𝐌𝐢𝐭𝐢𝐠𝐚𝐭𝐢𝐨𝐧:
Add guardrails. Human in the loop for high-risk steps. 
Easy opt-out. Monitor drift and complaints.

𝐄𝐱𝐢𝐭:
Define kill-switch rules. Set a sunset date. 
Plan a rollback so you can stop fast without chaos.

𝐘𝐨𝐮𝐫 “𝐒𝐡𝐨𝐮𝐥𝐝 𝐖𝐞?” 𝐌𝐞𝐞𝐭𝐢𝐧𝐠 𝐂𝐡𝐞𝐜𝐤𝐥𝐢𝐬𝐭:
Use in every approval meeting. One “No” means pause and fix.
✅ Clear user benefit a customer would recognise
✅ Informed consent for this specific data use
✅ Opt-out without penalty
✅ Bias tested on affected groups
✅ Outcome explainable in plain language
✅ Least data needed to deliver the benefit
✅ Named owner if something goes wrong
✅ Defined kill switch and owner
✅ Smallest safe pilot before scale
✅ Harm, complaints, and drift measured weekly

𝐖𝐡𝐲 𝐭𝐡𝐢𝐬 𝐦𝐚𝐭𝐭𝐞𝐫𝐬:
Trust is the ultimate advantage.
Ethics done first lowers risk, speeds adoption, and protects the brand.

P.S. What question would you add to the “Should we” checklist?

#Leadership #AI #Dataethics #Responsibleinnovation #Techleadership

When Ethics Walks Into the Room Before Your Data Does

𝐀𝐈 𝐂𝐡𝐚𝐧𝐠𝐞 𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐓𝐡𝐚𝐭 𝐒𝐮𝐫𝐯𝐢𝐯𝐞𝐬 𝐀𝐮𝐝𝐢𝐭

Most teams ship models like experiments, then struggle to prove who changed what, when, why, and with what risk.
Auditors do not care about hype. They care about evidence.

𝐓𝐡𝐞 𝐦𝐢𝐧𝐝𝐬𝐞𝐭
Treat models like code. Use a registry, versioning, rollback, bias and drift monitoring.

𝐓𝐡𝐞 𝐓𝐑𝐀𝐂𝐊 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤:

𝐓𝐫𝐢𝐠𝐠𝐞𝐫:
State why the change is needed, expected impact, and go or no-go criteria.

𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫:
Log the model with owner, purpose, data lineage, version, features, and training date.

𝐀𝐬𝐬𝐞𝐬𝐬:
Run automated tests for accuracy, fairness, safety and privacy. Compare to the last approved version.

𝐂𝐨𝐦𝐦𝐢𝐭:
Get risk and owner approval. Deploy with guardrails.

𝐊𝐞𝐞𝐩 𝐰𝐚𝐭𝐜𝐡:
Monitor live performance, drift, and bias. Define rollback rules in advance.

𝐂𝐨𝐧𝐭𝐫𝐨𝐥𝐬 𝐭𝐡𝐚𝐭 𝐬𝐮𝐫𝐯𝐢𝐯𝐞 𝐚𝐮𝐝𝐢𝐭
→ Model registry with version pinning and full lineage.
→ Change ticket with purpose, risk rating, and test results.
→ Staged rollout with shadow runs, then canary.
→ Kill switch with pre-agreed rollback plan.
→ Continuous monitors for data and output drift, bias.
→ Decision log that captures who approved, when, and why.
→ Evidence pack with model card, monitoring report, and rollback outcome.

𝐓𝐡𝐢𝐬 𝐢𝐬 𝐧𝐨𝐭 𝐫𝐞𝐝 𝐭𝐚𝐩𝐞. 
It protects customers, reduces risk, and passes the audit the first time.

P.S. What control has saved you in an audit or post-incident review? Share one practice below.

#Assuranceseries #AI #Modelgovernance #Compliance #Riskmanagement #Leadership

AI Change Control That Survives Audit

𝐌𝐨𝐬𝐭 𝐝𝐚𝐭𝐚 𝐩𝐫𝐨𝐠𝐫𝐚𝐦𝐬 𝐟𝐚𝐢𝐥 𝐛𝐞𝐜𝐚𝐮𝐬𝐞 𝐨𝐰𝐧𝐞𝐫𝐬𝐡𝐢𝐩 𝐬𝐭𝐚𝐲𝐬 𝐢𝐧𝐯𝐢𝐬𝐢𝐛𝐥𝐞.

Policies define roles. Visibility creates accountability.

𝐓𝐡𝐞 𝐬𝐡𝐢𝐟𝐭
Move from policy on paper to scorecards in practice.

𝐃𝐞𝐟𝐢𝐧𝐞 𝐜𝐥𝐞𝐚𝐫 𝐨𝐰𝐧𝐞𝐫𝐬𝐡𝐢𝐩
Make each domain’s owner explicit: what they own, what they decide, what they delegate. Publish it.

Starter scorecard you can launch this month
𝐐𝐮𝐚𝐥𝐢𝐭𝐲:
• % valid records on critical elements
• % completeness on key fields
• Failed quality checks closed per month

𝐑𝐞𝐭𝐞𝐧𝐭𝐢𝐨𝐧:
• % datasets with retention rules applied
• % expired data deleted on time
• Exceptions awaiting approval

𝐋𝐢𝐧𝐞𝐚𝐠𝐞:
• % critical data with end to end lineage
• % change requests with impact analysis
• Broken lineage links outstanding

𝐀𝐜𝐜𝐞𝐬𝐬:
• % users at least privilege
• % high-risk roles reviewed this quarter
• Mean time to revoke access after exit or role change

𝐎𝐩𝐞𝐫𝐚𝐭𝐞 𝐰𝐢𝐭𝐡 𝐒𝐞𝐞 → 𝐃𝐞𝐜𝐢𝐝𝐞 → 𝐀𝐜𝐭

𝐒𝐞𝐞:
Automate from catalog, quality checks, access logs. Show red, amber, green by owner and domain.

𝐃𝐞𝐜𝐢𝐝𝐞:
Set thresholds per KPI. Agree triggers, owners, and due dates. Link results to incentives and recognition.

𝐀𝐜𝐭:
Use short playbooks. Two week quality fixes. Thirty day access clean up. Quarterly lineage reviews. Recheck next cycle.

𝐖𝐡𝐲 𝐭𝐡𝐢𝐬 𝐰𝐨𝐫𝐤𝐬
 You cannot manage what you do not measure.
 Accountability moves from slogans to numbers.
 Risk and audit conversations get faster and calmer.
 Investment targets where it moves the needle.

𝐒𝐭𝐚𝐫𝐭 𝐬𝐦𝐚𝐥𝐥
One domain. Three KPIs. One published scorecard. Improve each cycle.

P.S. What KPI would you add to a data owner scorecard in your team?

Data Owner Scorecards: from policy to accountability

Stop starting. Start finishing: Portfolio Kanban with Board-level WIP limits

Most Boards drown the organisation in initiatives, then wonder why nothing finishes.

More starts do not create momentum. Flow does.

𝐇𝐨𝐰 𝐭𝐨 𝐫𝐮𝐧 𝐢𝐭:

1️⃣ 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐬𝐞 𝐭𝐡𝐞 𝐩𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨:
One Kanban board for all initiatives, in flight, paused, waiting. 
When leaders can see it, they can challenge it.

2️⃣ Set WIP limits by real capacity
Cap how many items can sit in Initiate, Plan, Build, and Deploy. If a column is full, new work waits.

3️⃣ 𝐀𝐝𝐨𝐩𝐭 𝐩𝐮𝐥𝐥, 𝐧𝐨𝐭 𝐩𝐮𝐬𝐡:
Teams start only when capacity is free, not when a sponsor asks.

4️⃣ 𝐔𝐬𝐞 𝐭𝐡𝐞 𝐍𝐞𝐱𝐭 𝐁𝐞𝐬𝐭 𝐓𝐡𝐢𝐧𝐠 𝐭𝐞𝐬𝐭:
 “If this is the most valuable thing right now, what do we finish or stop to make space?”
 No new starts without a finish.

5️⃣ Govern flow, not volume:
Track throughput and lead time. 
Fewer items in progress move faster.

6️⃣ 𝐀𝐩𝐩𝐥𝐲 𝐭𝐡𝐞 𝐅𝐢𝐧𝐢𝐬𝐡 𝐑𝐮𝐥𝐞:
When a column hits its limit, leaders choose: stop new starts, swap priorities, or split work to unblock flow.

𝐖𝐡𝐲 𝐢𝐭 𝐰𝐨𝐫𝐤𝐬
Higher throughput, shorter lead times, clearer priorities and less burnout.
𝐁𝐨𝐚𝐫𝐝𝐬 𝐭𝐡𝐚𝐭 𝐠𝐨𝐯𝐞𝐫𝐧 𝐟𝐥𝐨𝐰 𝐟𝐢𝐧𝐢𝐬𝐡 𝐦𝐨𝐫𝐞, 𝐟𝐚𝐬𝐭𝐞𝐫.

How does your organisation decide what to stop so the right work can finish?

 #WIPLimits #Portfoliokanban #Leadership #Strategyexecution #ProgramGovernance

Portfolio Kanban with Board-level WIP limits

𝐂𝐫𝐢𝐬𝐢𝐬 𝐜𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧: 𝟑𝐂𝐬 + 𝐒𝐀𝐓 𝐛𝐫𝐢𝐞𝐟

When everything is breaking, communication is the real control system.
Dashboards blur. What teams need most is calm direction.

𝟑𝐂𝐬

▶️ 𝐂𝐚𝐥𝐦
→ Say what is known, what is unknown and what is next. 
→ Never guess, never blame.

▶️ 𝐂𝐥𝐚𝐫𝐢𝐭𝐲
→ One channel, one owner, one message cadence. 
→ Confusion kills faster than failure.

▶️𝐂𝐫𝐞𝐝𝐢𝐛𝐢𝐥𝐢𝐭𝐲
→ Share numbers, not adjectives. 
→ Admit uncertainty, then update visibly as facts evolve.

𝐒𝐀𝐓 𝐛𝐫𝐢𝐞𝐟:
▶️ 𝐒𝐩𝐞𝐞𝐝
→ Issue a 60-second checkpoint every 10 minutes in the same room with the same owner.

▶️ 𝐀𝐜𝐜𝐮𝐫𝐚𝐜𝐲
→ Time-stamp each note. 
→ Separate facts from assumptions. 
→ Keep one source of truth.

▶️ 𝐓𝐨𝐧𝐞
→ Be specific and accountable. 
→ Say what will happen before the next checkpoint.

𝐖𝐡𝐲 𝐢𝐭 𝐰𝐨𝐫𝐤𝐬
Teams stay focused, not fearful, stakeholders trust the process, not promises, and leaders project control through structure, not slogans.

P.S. What message calmed your last major incident the fastest?

#Leadership #Crisiscommunication #Decisionmaking #Programleadership #Resilience #Changemanagement #Teamculture

Crisis communication: 3Cs + SAT brief

𝐒𝐡𝐚𝐝𝐨𝐰 𝐦𝐞𝐭𝐫𝐢𝐜𝐬 𝐯𝐬 𝐨𝐟𝐟𝐢𝐜𝐢𝐚𝐥 𝐧𝐮𝐦𝐛𝐞𝐫𝐬: 𝐞𝐧𝐝 𝐭𝐡𝐞 𝐦𝐞𝐭𝐫𝐢𝐜 𝐦𝐢𝐫𝐚𝐠𝐞

Most leaders are making critical decisions based on beautiful lies.
Dashboards look green. 
Operations tell a different story. The gap is the metric mirage.

𝐓𝐡𝐞 𝐬𝐡𝐢𝐟𝐭
Stop celebrating numbers that look good. 
Start validating numbers that are true.

𝐌𝐞𝐭𝐫𝐢𝐜 𝐫𝐞𝐚𝐥𝐢𝐭𝐲 𝐜𝐡𝐞𝐜𝐤:

𝐃𝐞𝐟𝐢𝐧𝐞 𝐛𝐞𝐟𝐨𝐫𝐞 𝐲𝐨𝐮 𝐝𝐞𝐜𝐢𝐝𝐞
→ Agree on what success means, not what looks good on slides. 
→ Write it down.

𝐒𝐚𝐦𝐩𝐥𝐞 𝐭𝐡𝐞 𝐬𝐨𝐮𝐫𝐜𝐞
→ Go beyond aggregates. 
→ Pull small, representative samples from real work every week.

𝐂𝐫𝐨𝐬𝐬-𝐫𝐞𝐟𝐞𝐫𝐞𝐧𝐜𝐞 𝐫𝐞𝐚𝐥𝐢𝐭𝐲
→ Compare official dashboards with the shadow metrics the teams use. 
→ Investigate every divergence.

𝐀𝐜𝐭 𝐨𝐧 𝐢𝐧𝐬𝐢𝐠𝐡𝐭𝐬
→ Decide based on reconciled truth. 
→ Fix the rule or fix the process.

𝐑𝐮𝐧 𝐭𝐡𝐢𝐬 𝐩𝐥𝐚𝐲𝐛𝐨𝐨𝐤 𝐭𝐡𝐢𝐬 𝐰𝐞𝐞𝐤:

𝐌𝐞𝐭𝐫𝐢𝐜 𝐜𝐡𝐚𝐫𝐭𝐞𝐫
Name, owner, purpose, unit of one, inclusions, exclusions, data source, refresh cadence.

𝐒𝐨𝐮𝐫𝐜𝐞 𝐨𝐟 𝐭𝐫𝐮𝐭𝐡
Pick one place that decides the number. If finance, CRM and PMO differ, choose the primary and log the rest as reference.

𝐂𝐨𝐮𝐧𝐭 𝐫𝐮𝐥𝐞
Show exactly how the number is created. Query or steps. If it cannot be repeated, it is not a rule.

𝐒𝐚𝐦𝐩𝐥𝐞 𝐚𝐧𝐝 𝐭𝐫𝐚𝐜𝐞
Choose 20 items per KPI weekly. Trace each from the dashboard to the record to the evidence. Mark pass or fail.

𝐕𝐚𝐫𝐢𝐚𝐧𝐜𝐞 𝐠𝐚𝐭𝐞
Set an allowed gap, for example, 2 percent. Above the gate, open a data defect and assign an owner and due date.

𝐃𝐮𝐚𝐥 𝐯𝐢𝐞𝐰 𝐫𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠
Two rows in the exec pack: official number and sample truth rate. When both are strong you can trust the story.

𝐊𝐞𝐲 𝐥𝐞𝐬𝐬𝐨𝐧𝐬
Clear definitions beat glossy charts.
Small weekly samples prevent big quarterly shocks.
One source of truth reduces debate and speeds decisions.
Variance gates turn hunches into action.

𝐒𝐭𝐚𝐫𝐭 𝐬𝐦𝐚𝐥𝐥
Pick your top three KPIs. Publish a one-page charter. Run the sampling loop for two weeks. Add the sample truth rate to the dashboard. Close variances within two sprints.

P.S. What metric in your world needs a charter and a weekly sample first?

Shadow metrics vs official numbers: end the metric mirage

𝐈𝐟 𝐭𝐫𝐮𝐭𝐡 𝐦𝐨𝐯𝐞𝐬 𝐬𝐥𝐨𝐰𝐞𝐫 𝐭𝐡𝐚𝐧 𝐫𝐢𝐬𝐤, 𝐑𝐎𝐈 𝐥𝐞𝐚𝐤𝐬 𝐪𝐮𝐢𝐞𝐭𝐥𝐲

Most teams do not lack talent.
They lack safe speed. People see issues, then wait.

Silence is costly. 
You pay in delays, rework, and churn.

𝐓𝐡𝐫𝐞𝐞 𝐬𝐩𝐞𝐚𝐤-𝐮𝐩 𝐫𝐢𝐭𝐮𝐚𝐥𝐬 𝐭𝐡𝐚𝐭 𝐦𝐚𝐤𝐞 𝐭𝐫𝐮𝐭𝐡 𝐭𝐫𝐚𝐯𝐞𝐥 𝐟𝐚𝐬𝐭𝐞𝐫 𝐭𝐡𝐚𝐧 𝐫𝐢𝐬𝐤:

𝟏) 𝐑𝐞𝐝-𝐅𝐥𝐚𝐠 𝐑𝐨𝐮𝐧𝐝:
→ Give five minutes at the start of each standup or leadership sync.
→ Anyone can raise one red flag using the impact, urgency, and owner fields.
→ Close with one next step per flag.

𝐑𝐞𝐬𝐮𝐥𝐭𝐬 𝐭𝐨 𝐭𝐫𝐚𝐜𝐤:
• Time to escalate: target 50% faster in 30 days
• Lead time on risks: surface risks two sprints earlier
• Blockers cleared per week: lift baseline by 20%

𝟐) 𝐃𝐢𝐬𝐬𝐞𝐧𝐭 𝐂𝐡𝐚𝐦𝐩𝐢𝐨𝐧:
→ Rotate one person each meeting to test the plan. 

𝐓𝐡𝐞𝐲 𝐦𝐮𝐬𝐭 𝐚𝐬𝐤:
• What would make this fail?
• Which assumption needs proof?
• What is the lowest cost test we can run this week?

𝐑𝐞𝐬𝐮𝐥𝐭𝐬 𝐭𝐨 𝐭𝐫𝐚𝐜𝐤:
• Surprise index: cut unplanned issues per sprint by 30%.
• Rework hours: reduce by 20% in a quarter.
• Decision quality: experiments run vs opinions adopted.

𝟑) 𝐑𝐞𝐯𝐞𝐫𝐬𝐚𝐥 𝐋𝐨𝐠:
→ Keep a simple log of key decisions, including the date, owners, assumptions, trigger for reversal, and outcome.
→ Review it biweekly. Celebrate fast course correction.

𝐑𝐞𝐬𝐮𝐥𝐭𝐬 𝐭𝐨 𝐭𝐫𝐚𝐜𝐤:
• Decision half-life: extend time before reversal as learning improves
• Repeat mistakes: drive toward zero repeats in two quarters
• Team retention: lift eNPS (Employee Net Promoter Score) and reduce regretted attrition by two to three points per quarter

𝐓𝐫𝐮𝐭𝐡-𝐅𝐢𝐫𝐬𝐭 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐥𝐨𝐨𝐩
𝐈𝐝𝐞𝐧𝐭𝐢𝐟𝐲: Which risks stay invisible if people are silent?
𝐈𝐧𝐯𝐢𝐭𝐞: use rituals to surface concerns early
𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐞: learn from the reversal log.
𝐃𝐞𝐜𝐢𝐝𝐞: act with the clearest information.
𝐌𝐨𝐧𝐢𝐭𝐨𝐫: track outcomes and adapt.

𝐖𝐡𝐲 𝐢𝐭 𝐦𝐚𝐭𝐭𝐞𝐫𝐬:
✅ Reduce operational and strategic risk
✅ Make faster, smarter decisions
✅ Build trust and psychological safety
✅ Convert candid insights into measurable ROI

P.S. How does your team ensure risks surface before they become crises?
P.S.S. Which speak-up ritual has paid off for you, and how did you measure it?
#Leadership #Decisionmaking #Culture #Operationalexcellence #Riskmanagement #Teamperformance

If truth moves slower than risk, ROI leaks quietly

𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞-𝐚𝐬-𝐂𝐨𝐝𝐞: 𝐓𝐮𝐫𝐧 𝐀𝐬𝐬𝐮𝐫𝐚𝐧𝐜𝐞 𝐢𝐧𝐭𝐨 𝐚 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞

A program I advised stalled for 6 weeks chasing audit evidence. 
Delivery paused. 
Morale dipped.

The fix was simple: move from paperwork to Governance-as-Code so the pipeline generates proof by itself.

𝐌𝐨𝐬𝐭 𝐭𝐞𝐚𝐦𝐬 𝐭𝐫𝐞𝐚𝐭 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐚𝐬 𝐩𝐚𝐩𝐞𝐫𝐰𝐨𝐫𝐤.
Policies sit in PDFs. Evidence appears at the end. Risk grows and delivery slows.

𝐇𝐞𝐫𝐞 𝐢𝐬 𝐚 𝐛𝐞𝐭𝐭𝐞𝐫 𝐩𝐚𝐭𝐡: codify guardrails and automate evidence inside your pipeline.
Ship faster, reduce risk, satisfy auditors without heroics.

𝐎𝐥𝐝 𝐯𝐬 𝐍𝐞𝐰
Old: manual reviews, spreadsheet checklists, evidence hunts at release time.
New: rules as code, checks in Continuous Integration, evidence captured on every run.

𝐓𝐑𝐀𝐂𝐄: 𝐓𝐮𝐫𝐧 𝐚𝐬𝐬𝐮𝐫𝐚𝐧𝐜𝐞 𝐢𝐧𝐭𝐨 𝐚 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞:

T → Translate policy into testable rules
Examples: encryption required, PII Masked, approved base images only.

R → Reinforce with guardrails in Continuous Integration.
Failing rule blocks the merge or raises a visible warning.

A → Automate evidence capture
Store pass or fail with timestamps, commit IDs and approver.

C → Control exceptions with expiry
Time-bound waivers, named owner, specific scope.

E → Expose results in dashboards
Show rule coverage, failure trends and open waivers.

𝐑𝐀𝐂𝐄: 𝐏𝐫𝐞-𝐫𝐞𝐥𝐞𝐚𝐬𝐞 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐜𝐡𝐞𝐜𝐤:

R → Risk level of the change
A → Alignment to policy and standards
C → Controls that passed or failed
E → Evidence that proves the state right now

𝐑𝐞𝐥𝐞𝐚𝐬𝐞 𝐢𝐟 𝐫𝐢𝐬𝐤 𝐢𝐬 𝐥𝐨𝐰 𝐚𝐧𝐝 𝐜𝐨𝐧𝐭𝐫𝐨𝐥𝐬 𝐩𝐚𝐬𝐬.
Delay or add mitigations if risk is high or evidence is weak.

𝐖𝐡𝐚𝐭 𝐭𝐞𝐚𝐦𝐬 𝐥𝐞𝐚𝐫𝐧 𝐪𝐮𝐢𝐜𝐤𝐥𝐲:
✅ Put rules where developers live, not in a policy portal.
✅ Make the secure path the easy path with templates and approved images.
✅ Treat evidence as a product artifact, not an afterthought.
✅ Review waivers weekly so that temporary does not become permanent.

𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐬𝐡𝐨𝐮𝐥𝐝 𝐬𝐩𝐞𝐞𝐝 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐲, 𝐧𝐨𝐭 𝐬𝐥𝐨𝐰 𝐢𝐭.
Turn your assurance into a pipeline and let the code prove the control.

P.S. What rule would you automate first?

#Assuranceseries #Riskmanagement #Compliance #Devops #Leadership

Governance-as-Code: Turn Assurance into a Pipeline

𝟓 𝐦𝐢𝐧𝐮𝐭𝐞𝐬 𝐯𝐬 𝟓𝟎 𝐦𝐢𝐧𝐮𝐭𝐞𝐬: 𝐛𝐮𝐢𝐥𝐝 𝐚 𝐤𝐢𝐥𝐥-𝐬𝐰𝐢𝐭𝐜𝐡 𝐜𝐮𝐥𝐭𝐮𝐫𝐞

Most teams panic when production wobbles. 
The best teams treat rollback like changing lanes. 
Deliberate, practised, routine.

𝐁𝐞𝐜𝐚𝐮𝐬𝐞 𝐩𝐚𝐧𝐢𝐜, 𝐧𝐨𝐭 𝐟𝐚𝐢𝐥𝐮𝐫𝐞, 𝐢𝐬 𝐭𝐡𝐞 𝐫𝐞𝐚𝐥 𝐨𝐮𝐭𝐚𝐠𝐞. 
The goal is not perfect systems. It is unshakeable confidence in recovery.

𝐀𝐝𝐨𝐩𝐭 𝐭𝐡𝐞 𝟓 𝐯𝐬 𝟓𝟎 𝐫𝐮𝐥𝐞
If key signals stay red for five minutes, roll back to protect the next fifty.

𝐖𝐡𝐚𝐭 𝐭𝐨 𝐢𝐧𝐬𝐭𝐢𝐭𝐮𝐭𝐢𝐨𝐧𝐚𝐥𝐢𝐬𝐞:

• 𝐂𝐥𝐞𝐚𝐫 𝐚𝐮𝐭𝐡𝐨𝐫𝐢𝐭𝐲:
Name the person who can pull the switch below the C-suite. 
No late-night debates. 
Clarity saves minutes. Minutes save millions.

• 𝐑𝐞𝐠𝐮𝐥𝐚𝐫 𝐫𝐞𝐡𝐞𝐚𝐫𝐬𝐚𝐥𝐬:
Run monthly 30-minute rollback drills in a production-like environment. Build muscle memory and surface missing scripts early.

• 𝐌𝐞𝐚𝐧𝐢𝐧𝐠𝐟𝐮𝐥 𝐢𝐧𝐬𝐭𝐫𝐮𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧:
Set go or no-go signals that show user impact in minutes. 
Automatic triggers, visible error budgets, and real-time audit evidence.

𝐖𝐡𝐲 𝐭𝐡𝐢𝐬 𝐰𝐨𝐫𝐤𝐬
Teams that practise stabilise in five minutes. 
Teams that wing it burn fifty and trust evaporates.

𝐘𝐨𝐮𝐫 𝐦𝐨𝐯𝐞:
P.S. Would you pass a rollback audit in your portfolio today? 
P.S.S. What does authority look like in your programs?

#Rollbackculture #Transformationleadership #Resilience #DevOps

5 minutes vs 50 minutes: build a kill-switch culture

Most boards design teams for headcount. The best design for decisions.
Measure decision lead time like you measure delivery lead time.

𝐏𝐥𝐚𝐲𝐛𝐨𝐨𝐤 𝐟𝐨𝐫 𝐭𝐡𝐢𝐬 𝐰𝐞𝐞𝐤

𝐌𝐚𝐩 𝐭𝐡𝐞 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬 𝐭𝐡𝐚𝐭 𝐮𝐧𝐛𝐥𝐨𝐜𝐤 𝐯𝐚𝐥𝐮𝐞
↳ List the top ten recurring calls that stall delivery. 
↳ Note owner, inputs, risk level, time limit.

𝐀𝐬𝐬𝐢𝐠𝐧 𝐬𝐢𝐧𝐠𝐥𝐞-𝐩𝐨𝐢𝐧𝐭 𝐨𝐰𝐧𝐞𝐫𝐬𝐡𝐢𝐩
↳ Consult many, decide one. 
↳ Publish who decides what and where authority lies.

𝐒𝐞𝐭 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐒𝐋𝐀𝐬 𝐚𝐧𝐝 𝐠𝐮𝐚𝐫𝐝𝐫𝐚𝐢𝐥𝐬
↳ Low risk 24 hours. Medium risk 72 hours. 
↳ High risk via a pre-booked weekly forum. 
↳ Pre-authorise spend thresholds, standards and risk limits to avoid repeat approvals.

𝐑𝐮𝐧 𝐚 𝐝𝐚𝐢𝐥𝐲 𝟏𝟓-𝐦𝐢𝐧𝐮𝐭𝐞 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐡𝐮𝐝𝐝𝐥𝐞
↳ Surface blocked items. Decide in the room. 
↳ Escalate only by exception.

𝐊𝐞𝐞𝐩 𝐭𝐡𝐞 𝐜𝐨𝐫𝐞 𝐭𝐞𝐚𝐦 𝐬𝐦𝐚𝐥𝐥 𝐚𝐧𝐝 𝐜𝐫𝐨𝐬𝐬-𝐟𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐚𝐥
↳ Product, delivery, engineering, risk. 
↳ Enough to decide, not enough to stall.

𝐂𝐚𝐬𝐞
A large program cut its core group from 14 to 8, named decision owners and delegated spend within guardrails.

Average approval time fell 60% in six weeks. Ship dates moved forward because work no longer waited for permission.

𝐌𝐞𝐭𝐫𝐢𝐜𝐬 𝐭𝐨 𝐭𝐫𝐚𝐜𝐤:
→ Decision lead time
→ Percent of decisions made within SLA
→ Escalation rate by decision type
→ Time in queue vs time to implement

𝐊𝐞𝐲 𝐥𝐞𝐬𝐬𝐨𝐧𝐬
Velocity is the new capacity.
Capacity adds bodies. Decision rights remove delays.

𝐓𝐡𝐞 𝐩𝐫𝐨𝐛𝐥𝐞𝐦
Layers create handoffs, queues and rework. 
Approvals bounce between forums.
Teams execute fast, but the work waits for signoff.

𝐓𝐡𝐞 𝐬𝐡𝐢𝐟𝐭
Stop asking if you have enough people. Start asking if the right people have the right decision rights.

𝐓𝐡𝐞 𝐢𝐝𝐞𝐚
Build teams around clear decision rights. 
Give the smallest capable group power to decide at the point of work.
Decision clarity beats extra headcount.
SLAs create flow.
Fewer intersections mean fewer delays.

𝐒𝐭𝐚𝐫𝐭 𝐧𝐨𝐰
→ This week map your top ten decisions, assign owners, set SLAs.
→ Next week run the daily huddle, shrink the room, measure lead time.
→ Report to the board on decisions made, average lead time and the oldest blocked decision.

P.S. What changed most when a smaller empowered team moved faster in your organisation?

#Decisionmaking #Agileleadership #Portfoliodelivery #ProgramDelivery #Digitaltransformation

𝐓𝐡𝐞 𝐈𝐧𝐯𝐢𝐬𝐢𝐛𝐥𝐞 𝐂𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐨𝐫𝐬: 𝐆𝐢𝐯𝐞 𝐒𝐡𝐚𝐝𝐨𝐰 𝐓𝐞𝐚𝐦𝐬 𝐚 𝐅𝐚𝐜𝐞 𝐚𝐧𝐝 𝐚 𝐕𝐨𝐢𝐜𝐞

The work you ship at 9 am was built at 2 am by people your board has never met.

If those teams are invisible, risk stays invisible too.
External and offshore pods carry the real delivery load.

Yet they often sit outside governance. Names are missing. Time zones clash. Access is unclear. Escalation feels unsafe.

𝐓𝐡𝐞 𝐦𝐢𝐧𝐝𝐬𝐞𝐭 𝐬𝐡𝐢𝐟𝐭:
→ Visibility is not bureaucracy.
→ It is how you keep speed without gambling on luck.
→ Give every pod a face, a clock and a clear path to raise risk.

𝐓𝐑𝐀𝐂𝐄: 𝐩𝐥𝐮𝐠 𝐬𝐡𝐚𝐝𝐨𝐰 𝐭𝐞𝐚𝐦𝐬 𝐢𝐧𝐭𝐨 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐤𝐢𝐥𝐥𝐢𝐧𝐠 𝐚𝐠𝐢𝐥𝐢𝐭𝐲:

𝐓𝐞𝐚𝐦 𝐦𝐚𝐩:
List names, roles, skills, location and time zone on one page. 
Add overlap windows so people know when to talk live.

𝐑𝐢𝐬𝐤 𝐫𝐨𝐮𝐭𝐞𝐬:
Make risk thresholds explicit. 
Define who to ping for P1 and P2 and the on-call chain. 
State that early flags are no blame.

𝐀𝐜𝐜𝐞𝐬𝐬 𝐚𝐥𝐢𝐠𝐧𝐦𝐞𝐧𝐭:
Map systems, environments and permissions for the pod. 
Use least privilege. 
Set a same-day SLA for access requests so work does not stall.

𝐂𝐚𝐝𝐞𝐧𝐜𝐞 𝐭𝐡𝐚𝐭 𝐟𝐢𝐭𝐬 𝐭𝐡𝐞 𝐜𝐥𝐨𝐜𝐤:
Keep a 15-minute overlap standup for handover. 
Use a weekly demo for flow health. 
Add a light governance checkpoint every two weeks tied to outcomes, not slides.

𝐄𝐯𝐢𝐝𝐞𝐧𝐜𝐞 𝐭𝐫𝐚𝐢𝐥:
Link decisions, PRs, tests and runbooks in one space. 
If a risk is flagged, capture cause, choice and fix within 24 hours.

𝐀 𝐟𝐢𝐯𝐞-𝐦𝐢𝐧𝐮𝐭𝐞 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐟𝐫𝐚𝐦𝐞 𝐟𝐨𝐫 𝐟𝐚𝐬𝐭 𝐞𝐬𝐜𝐚𝐥𝐚𝐭𝐢𝐨𝐧𝐬

𝐏𝐀𝐃:
𝐏𝐫𝐨𝐛𝐥𝐞𝐦: What is at risk in plain words
𝐀𝐥𝐭𝐞𝐫𝐧𝐚𝐭𝐢𝐯𝐞𝐬: two options with impact and time needed
𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧: who decides now, and what we will measure next

𝐖𝐡𝐲 𝐭𝐡𝐢𝐬 𝐰𝐨𝐫𝐤𝐬:
People know who to call and when.
Access does not block work.
Risks surface early while fixes are still cheap.
Leaders see real delivery, not a filtered version.

𝐒𝐭𝐚𝐫𝐭 𝐭𝐡𝐢𝐬 𝐰𝐞𝐞𝐤:
Create a one-page roster with names, time zones and overlap windows.
Add an access map for your top two critical systems.
Run PAD on the following incident and publish the note

P.S. How do you keep offshore pods visible and safe to escalate risk?

#Leadership #Programdelivery #Offshoreteams #Governance #Strategicexecution #Digitaltransformation

𝐊𝐞𝐞𝐩 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐖𝐡𝐞𝐧 𝐕𝐞𝐧𝐝𝐨𝐫𝐬 𝐄𝐱𝐢𝐭: 𝐀 𝐏𝐞𝐨𝐩𝐥𝐞-𝐅𝐢𝐫𝐬𝐭 𝐏𝐥𝐚𝐲𝐛𝐨𝐨𝐤

Knowledge does not live in contracts. It lives in people.
When a vendor leaves, the real risk is lost know-how.
Avoid weekend heroics and fragile handovers with a clear plan.

𝐏𝐀𝐂𝐓: 𝐭𝐡𝐞 𝐞𝐱𝐢𝐭 𝐜𝐡𝐞𝐜𝐤𝐥𝐢𝐬𝐭

𝐏𝐞𝐨𝐩𝐥𝐞:
Name the humans who hold critical know-how and pair each with an internal owner.

 𝐀𝐜𝐜𝐞𝐬𝐬:
List every account, key and tool. Decide who gets what and when it changes.

𝐂𝐫𝐢𝐭𝐢𝐜𝐚𝐥 𝐤𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞:
Capture the real steps, not just the happy path.

𝐓𝐢𝐦𝐞𝐥𝐢𝐧𝐞:
Set dates for overlap, rehearsal and final cut.
Use PACT to approve, defer or escalate.

𝟑-𝐑: 𝐰𝐡𝐚𝐭 𝐭𝐨 𝐤𝐞𝐞𝐩, 𝐜𝐥𝐨𝐧𝐞 𝐨𝐫 𝐫𝐞𝐦𝐨𝐯𝐞
𝐑𝐞𝐭𝐚𝐢𝐧:
Safeguard must-keep knowledge with owners and back-ups.

Replicate:
Record live walk-throughs so successors learn context.

𝐑𝐞𝐭𝐢𝐫𝐞:
Kill obsolete processes and access to cut complexity.

𝐒𝐢𝐱-𝐰𝐞𝐞𝐤 𝐡𝐚𝐧𝐝𝐨𝐯𝐞𝐫 𝐩𝐥𝐚𝐧:
𝐖𝐞𝐞𝐤 𝟏: 
Map systems and single points of failure. Pick owners. Set PACT.

𝐖𝐞𝐞𝐤 𝟐: 
Buddy vendor and internal leads. Record walk-throughs. Start runbooks.

𝐖𝐞𝐞𝐤 𝟑: 
Swap seats. Internal drives while the vendor observes. Fix doc gaps.

𝐖𝐞𝐞𝐤 𝟒: 
Rehearse end-to-end, including on-call. Time each step.

𝐖𝐞𝐞𝐤 𝟓: 
Pre-provision accounts. Rotate keys. Remove vendor access on joint sign-off.

𝐖𝐞𝐞𝐤 𝟔 : 
Run solo for one week. Track incidents and time to restore. Close when quality holds.

𝐂𝐨𝐦𝐦𝐨𝐧 𝐝𝐫𝐚𝐢𝐧𝐬 𝐚𝐧𝐝 𝐪𝐮𝐢𝐜𝐤 𝐟𝐢𝐱𝐞𝐬:
▶️ Late transfer → shallow notes and 2 a.m. calls → record live sessions and build runbooks
▶️ No overlap → one person burns out → backfill early and rotate on-call
▶️ Messy access → locked accounts and stalled releases → inventory access, stage new accounts and rotate secrets.

𝐖𝐡𝐲 𝐭𝐡𝐢𝐬 𝐰𝐨𝐫𝐤𝐬:
It protects people, reduces risk and keeps delivery steady.

P.S. What part of exits hurts most in your world, knowledge transfer, backfills or access?

#Leadership #Knowledgemanagement #Vendormanagement  #Programdelivery

Keep Knowledge When Vendors Exit: A People-First Playbook

𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐫𝐞𝐬𝐢𝐥𝐢𝐞𝐧𝐜𝐞 𝐬𝐭𝐚𝐫𝐭𝐬 𝐰𝐢𝐭𝐡 𝐭𝐞𝐚𝐦 𝐫𝐞𝐬𝐢𝐥𝐢𝐞𝐧𝐜𝐞

Uncertain markets test portfolios. 
Portfolios fail when teams fail.

We learned this when a critical stream looked fine on status, yet signals told a different story.

𝐑𝐞𝐬𝐢𝐥𝐢𝐞𝐧𝐜𝐞 𝐃𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝: 𝐰𝐡𝐚𝐭 𝐭𝐨 𝐰𝐚𝐭𝐜𝐡
→ Quality dips and rising defect escape
→ Set realistic WIP limits by true capacity.
→ Measure flow and predictability, not busyness

→ 𝐂𝐚𝐬𝐞: 𝐚𝐯𝐨𝐢𝐝𝐢𝐧𝐠 𝐚 𝟓𝐌 𝐝𝐞𝐥𝐚𝐲
Velocity down 18%, defects up, retros quiet.
Inquiry exposed context switching across three initiatives and unclear priorities.
RVelocity drops across two or more sprints

→ Silence in retros and low psychological safety
→ Unplanned work ratio rising and after-hours commits
→ Backlog churn and priority flips
→ PTO spikes, attrition risk, onboarding drag

𝐒𝐈𝐑 𝐥𝐨𝐨𝐩: 𝐚 𝐬𝐢𝐦𝐩𝐥𝐞 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤:

𝐒𝐢𝐠𝐧𝐚𝐥: 
→ Read the dashboard weekly. 
→ Confirm the trend across two cycles.

𝐈𝐧𝐪𝐮𝐢𝐫𝐲: 
→ Ask what changed, what is blocked, and what support is needed. 
→ Listen to the team lead and the team.

𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐞: 
→ Pick the smallest fix with the biggest lift. 
→ Reduce WIP to a hard cap. Freeze scope for one sprint. 
→ Swap a meeting for a maker block. 
→ Add a staff engineer for reviews. Recheck next week.

𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐦𝐞𝐜𝐡𝐚𝐧𝐢𝐜𝐬 𝐭𝐡𝐚𝐭 𝐦𝐚𝐤𝐞 𝐢𝐭 𝐬𝐭𝐢𝐜𝐤
→  Visualise everything on a single Portfolio Kanban board.
→  Response set a two-item WIP cap, ran a Decision Day to reset priorities, and re-planned vendor handoffs. 
→  Signals recovered in two sprints, and the release held its date.

𝐓𝐫𝐲 𝐭𝐡𝐢𝐬 𝐰𝐞𝐞𝐤:
Publish a one-page dashboard per stream. 
Review it every Tuesday in the portfolio stand-up. 
Run one SIR loop.

P.S. What signal on your teams predicts trouble the earliest?

#Portfolioresilience #Teamresilience #WIPlimits #Portfoliokanban #Leadership #Strategyexecution

Portfolio resilience starts with team resilience

𝐅𝐫𝐚𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐯𝐬 𝐟𝐮𝐥𝐥-𝐭𝐢𝐦𝐞 𝐢𝐬 𝐧𝐨𝐭 𝐭𝐡𝐞 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧

Boards think the choice is salary vs day rate.
The real question is ROI vs time to impact.

𝐓𝐡𝐞 𝐬𝐡𝐢𝐟𝐭
Match the model to horizon, risk and depth of change. Not to preference.

𝐖𝐡𝐞𝐫𝐞 𝐟𝐫𝐚𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐰𝐢𝐧𝐬:
→ Short horizon outcomes, 30 to 180 days
→ Spiky expertise you do not need forever
→ Turnaround, interim cover, due diligence, program reset
→ Variable cost when budgets are tight

𝐖𝐡𝐞𝐫𝐞 𝐟𝐮𝐥𝐥 𝐭𝐢𝐦𝐞 𝐰𝐢𝐧𝐬:
→ Multi year change that touches culture and operating model
→ Large teams, cross functional dependencies, deep stakeholder management
→ Enduring capabilities, succession, leadership bench
→ Stable budget with a long runway

𝐁𝐎𝐀𝐑𝐃 𝐟𝐢𝐭 𝐭𝐞𝐬𝐭 𝐟𝐨𝐫 𝐝𝐢𝐫𝐞𝐜𝐭𝐨𝐫𝐬:
→ 𝐁𝐮𝐝𝐠𝐞𝐭 𝐞𝐥𝐚𝐬𝐭𝐢𝐜𝐢𝐭𝐲. 
If you need flexible cost, lean fractional

𝐎𝐮𝐭𝐜𝐨𝐦𝐞 𝐡𝐨𝐫𝐢𝐳𝐨𝐧. 
→ If wins must land in 1 to 2 quarters, lean fractional.

→ 𝐀𝐜𝐜𝐨𝐮𝐧𝐭𝐚𝐛𝐢𝐥𝐢𝐭𝐲. 
If you need one owner through to BAU, lean full time.

→ 𝐑𝐚𝐭𝐞 𝐨𝐟 𝐜𝐡𝐚𝐧𝐠𝐞. 
If the market is moving weekly, lean fractional to stay adaptive.

→ 𝐃𝐞𝐩𝐭𝐡 𝐨𝐟 𝐜𝐡𝐚𝐧𝐠𝐞. 
If you are rewiring core systems and culture, lean full time

𝐑𝐎𝐈 𝐢𝐧 𝐩𝐥𝐚𝐢𝐧 𝐄𝐧𝐠𝐥𝐢𝐬𝐡:
𝐅𝐫𝐚𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐑𝐎𝐈→ Pay for outcomes, not permanence. Faster start, lower fixed cost, clear 90 day value checks

𝐅𝐮𝐥𝐥 𝐭𝐢𝐦𝐞 𝐑𝐎𝐈→ Pay for compounding effects. Org design, capability build, long memory, stable leadership signal

𝐑𝐞𝐜𝐫𝐮𝐢𝐭𝐞𝐫 𝐬𝐢𝐠𝐧𝐚𝐥 𝐜𝐡𝐞𝐜𝐤:
𝐅𝐫𝐚𝐜𝐭𝐢𝐨𝐧𝐚𝐥→ Day one plan in two pages, clear 30 60 90 outcomes, start within two weeks, strong cross industry references, simple conversion terms

𝐅𝐮𝐥𝐥 𝐭𝐢𝐦𝐞→ A 12 to 24 month roadmap, evidence of team build and succession, operating cadence you have run before, proof you work the boardroom and the floor

𝐃𝐞𝐜𝐢𝐝𝐞 𝐭𝐡𝐢𝐬 𝐰𝐞𝐞𝐤
→ Write the outcome in one sentence with a date and owner
→ Score each BOARD factor high or low
→ If budget elastic or horizon short or rate of change high, choose fractional
→ If depth of change high or accountability end to end, choose full time


You are not choosing a title. 
𝐘𝐨𝐮 𝐚𝐫𝐞 𝐜𝐡𝐨𝐨𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐟𝐚𝐬𝐭𝐞𝐬𝐭 𝐩𝐚𝐭𝐡 𝐭𝐨 𝐝𝐮𝐫𝐚𝐛𝐥𝐞 𝐯𝐚𝐥𝐮𝐞.

Pick the model that matches your horizon, risk and depth of change.

P.S. What worked best for your board in the last year, fractional or full time? Share the context and why.

Fractional vs full-time is not the question

Most programs do not fail on strategy.
They stall on sponsor energy.

𝐓𝐰𝐨 𝐬𝐩𝐨𝐧𝐬𝐨𝐫𝐬 𝐜𝐚𝐧 𝐬𝐡𝐚𝐫𝐞 𝐭𝐡𝐞 𝐬𝐚𝐦𝐞 𝐭𝐢𝐭𝐥𝐞.
One fuels momentum.
One drains it.

𝐇𝐞𝐫𝐞 𝐢𝐬 𝐭𝐡𝐞 𝐦𝐢𝐧𝐝𝐬𝐞𝐭 𝐭𝐡𝐚𝐭 𝐜𝐡𝐚𝐧𝐠𝐞𝐝 𝐦𝐲 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡:
Treat sponsor behavior as a force you can map and move.

𝐄𝐧𝐞𝐫𝐠𝐲 × 𝐈𝐧𝐟𝐥𝐮𝐞𝐧𝐜𝐞 𝐥𝐞𝐧𝐬
Plot each sponsor on two axes
Energy: fuels or drains
Influence: high or low

High energy × high influence → Accelerator
High energy × low influence → Supporter
Low energy × high influence → Brake
Low energy × low influence → Absence

Your risk lives in the Brake quadrant.
Your leverage lives in the Accelerator quadrant.

𝟑-𝐬𝐭𝐞𝐩 𝐬𝐜𝐫𝐢𝐩𝐭 𝐭𝐨 𝐜𝐨𝐧𝐯𝐞𝐫𝐭 𝐚 𝐥𝐨𝐰-𝐞𝐧𝐞𝐫𝐠𝐲 𝐬𝐩𝐨𝐧𝐬𝐨𝐫 𝐢𝐧𝐭𝐨 𝐚 𝐛𝐥𝐨𝐜𝐤𝐞𝐫 𝐫𝐞𝐦𝐨𝐯𝐞𝐫

𝟏. 𝐍𝐚𝐦𝐞 𝐭𝐡𝐞 𝐬𝐭𝐮𝐜𝐤 𝐩𝐨𝐢𝐧𝐭 𝐰𝐢𝐭𝐡 𝐨𝐧𝐞 𝐦𝐞𝐭𝐫𝐢𝐜
→ “We are slipping two weeks due to cross-team approvals.”

𝟐. 𝐌𝐚𝐤𝐞 𝐚 𝐬𝐢𝐧𝐠𝐥𝐞, 𝐜𝐨𝐧𝐜𝐫𝐞𝐭𝐞 𝐚𝐬𝐤
→ “I need you to clear Approval X with Finance by Wednesday.”

𝟑. 𝐎𝐟𝐟𝐞𝐫 𝐭𝐡𝐞 𝐬𝐡𝐨𝐫𝐭𝐞𝐬𝐭 𝐩𝐚𝐭𝐡
→ “I drafted the note. If you approve it now, I will send it and track it.  I will brief you in 48 hours.”
→ Keep it specific, time-bound and easy to act on.

𝐀 𝐬𝐢𝐦𝐩𝐥𝐞 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐟𝐫𝐚𝐦𝐞 𝐟𝐨𝐫 𝐬𝐩𝐨𝐧𝐬𝐨𝐫 𝐡𝐮𝐝𝐝𝐥𝐞𝐬:

Use this five-minute loop whenever the team is blocked
𝐈𝐬𝐬𝐮𝐞 → What is the one blocker
𝐈𝐦𝐩𝐚𝐜𝐭 → cost to time, cost to value
𝐎𝐩𝐭𝐢𝐨𝐧 𝐀 𝐨𝐫 𝐁 → show the trade in one line
𝐎𝐰𝐧𝐞𝐫 → who decides today
𝐍𝐞𝐱𝐭 𝐬𝐭𝐞𝐩 → what happens by when

This keeps energy pointed at outcomes, not meetings.

𝐖𝐡𝐲 𝐭𝐡𝐢𝐬 𝐦𝐚𝐭𝐭𝐞𝐫𝐬
→ Programs rise on sponsor energy, access and follow-through.
→ Map the energy.
→ Focus your asks.

𝐓𝐮𝐫𝐧 𝐛𝐫𝐚𝐤𝐞𝐬 𝐢𝐧𝐭𝐨 𝐚𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐨𝐫𝐬.

P.S. What sponsor behaviour has most helped or hurt your delivery? Share one example so we can all learn.

Taplio

Punardeep Singh's Linkedin Analytics

Punardeep Singh

Performance ScorePunardeep Singh's LinkedIn Performance

Punardeep Singh's Best Posts (last 30 days)

Ready to grow your LinkedIn presence?

Taplio

.css-6ytdur{background-image:linear-gradient(284deg, rgba(39, 43, 72, 1) 0%, rgba(33, 47, 183, 1) 100%);color:transparent;-webkit-background-clip:text;background-clip:text;}Punardeep Singh's Linkedin Analytics

Punardeep Singh

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Punardeep Singh's LinkedIn Performance

Punardeep Singh's Best Posts .css-1emoo84{font-size:var(--chakra-fontSizes-md);font-weight:400;color:var(--chakra-colors-gray-600);}(last 30 days)

Ready to grow your LinkedIn presence?

Punardeep Singh's Linkedin Analytics

Performance ScorePunardeep Singh's LinkedIn Performance

Punardeep Singh's Best Posts (last 30 days)