Project Risk Assessment Techniques

Most projects fail. But there’s a simple technique to give yours a fighting chance. It’s not a to-do list. It’s not a fancy tool. It’s not a 12-step system. It’s a single question that flips the way you think. Here’s how it works: It’s called a “premortem.” You’ve heard of a postmortem what went wrong after a project dies. A premortem asks: What if we ran that analysis now? Before anything dies. Before the first misstep. Before failure sets in. The premortem comes from psychologist Gary Klein. Here’s how to run one: → Gather your team. → Imagine it’s 2 years in the future. → The project has completely failed. → Ask: What went wrong? No sugarcoating. No happy talk. Start listing the causes of failure. Budget misfire? Wrong team? Lack of buy-in? Scope creep? Missed deadlines? You’ll be shocked how quickly people identify risks—once they feel safe predicting failure. Why this works: It defeats irrational optimism. • It turns hindsight into foresight. • It makes risk visible. • It aligns the team before chaos hits. Because the best time to fix a problem… is before it happens. Pre-mortems don’t require special skills. Just a shift in mindset: Don’t assume success. Assume failure—and reverse-engineer your way out. Ask: What will future-you wish you had done? Then… do that now. I run a premortem for every big project I take on. Writing a book? Premortem. Launching a podcast? Premortem. Planning an event? Premortem. It never guarantees success—but it always makes success more likely. Summary: The Premortem Playbook → Imagine future failure. → List the causes. → Turn those risks into action steps. → Adjust your plan today. It’s one of the most underrated tools in your productivity toolkit. Try it before your next project. You won’t regret it.

Your AI project will succeed or fail before a single model is deployed. The critical decisions happen during vendor selection — especially in fintech where the consequences of poor implementation extend beyond wasted budgets to regulatory exposure and customer trust. Financial institutions have always excelled at vendor risk management. The difference with AI? The risks are less visible and the consequences more profound. After working on dozens of fintech AI implementations, I've identified four essential filters that determine success when internal AI capabilities are limited: 1️⃣ Integration Readiness For fintech specifically, look beyond the demo. Request documentation on how the vendor handles system integrations. The most advanced AI is worthless if it can't connect to your legacy infrastructure. 2️⃣ Interpretability and Governance Fit In financial services, "black box" AI is potentially non-compliant. Effective vendors should provide tiered explanations for different stakeholders, from technical teams to compliance officers to regulators. Ask for examples of model documentation specifically designed for financial service audits. 3️⃣ Capability Transfer Mechanics With 71% of companies reporting an AI skills gap, knowledge transfer becomes essential. Structure contracts with explicit "shadow-the-vendor" periods where your team works alongside implementation experts. The goal: independence without expertise gaps that create regulatory risks. 4️⃣ Road-Map Transparency and Exit Options Financial services move slower than technology. Ensure your vendor's development roadmap aligns with regulatory timelines and includes established processes for model updates that won't trigger new compliance reviews. Document clear exit rights that include data migration support. In regulated industries like fintech, vendor selection is your primary risk management strategy. The most successful implementations I've witnessed weren't led by AI experts, but by operational leaders who applied these filters systematically, documenting each requirement against specific regulatory and business needs. Successful AI implementation in regulated industries is fundamentally about process rigor before technical rigor. #fintech #ai #governance

Here's my cheat sheet for a first-pass quantitative risk assessment. Use this as your “day-one” playbook when leadership says: “Just give us a first pass. How bad could this get?” 1. Frame the business decision - Write one sentence that links the decision to money or mission. Example: “Should we spend $X to prevent a ransomware-driven hospital shutdown?” 2. Break the decision into a risk statement - Identify the chain: Threat → Asset → Effect → Consequence. Capture each link in a short phrase. Example: “Cyber criminal group → business email → data locked → widespread outage” 3. Harvest outside evidence for frequency and magnitude - Where has this, or something close, already happened? Examples: Industry base rates, previous incidents and near misses from your incident response team, analogous incidents in other sectors 4. Fill the gaps with calibrated experts - Run a quick elicitation for frequency and magnitude (5th, 50th, and 95th percentiles). - Weight experts by calibration scores if you have them; use a simple average if you don’t. 5. Assemble priors and simulate - Feed frequencies and losses into a Monte Carlo simulation. Use Excel, Python, R, whatever’s handy. 6. Stress-test the story - Host a 30-minute premortem: “It’s a year from now. The worst happened. What did we miss?” - Adjust inputs or add/modify scenarios, then re-run the analysis. 7. Deliver the first-cut answer - Provide leadership with executive-ready extracts. Examples: Range: “10% chance annual losses exceed $50M.” Sensitivity drivers: Highlight the inputs that most affect tail loss Value of information: Which dataset would shrink uncertainty fastest. Done. You now have a defensible, numbers-based initial assessment. Good enough for a go/no-go decision and a clear roadmap for deeper analysis. This fits on a sticky note. #riskassessment #RiskManagement #cyberrisk

Risk Management Made Simple: A Straightforward Approach for Every Project Manager Risk management is crucial to project success, yet it's often seen as complex and intimidating. Here’s a simple approach to managing risks in your projects: 1/ Identify Risks Early: → Start with a risk brainstorm: technical, operational, financial, and external risks. → Collaborate with your team to identify potential threats and opportunities. → Involve diverse team members to gain different perspectives on possible risks. → Use historical data and past project experiences to spot risks that may arise again. 2/ Assess and Prioritize: → Use a risk matrix to assess impact and likelihood. → Prioritize high-impact risks that could derail your project’s success. → Make sure you reassess risks periodically to capture any changes in impact or probability. → Don’t forget to consider opportunities as well—these should be prioritized, too! 3/ Develop Mitigation Plans: → For each priority risk, develop a strategy to minimize or avoid it. → Plan for contingencies to stay prepared for the unexpected. → Ensure the mitigation plans are realistic and actionable. → Set up early-warning systems so you can act quickly if needed. 4/ Assign Ownership: → Assign a team member to own each risk, ensuring accountability. → Ensure they track progress and adjust strategies as necessary. → Empower the risk owner with resources and authority to implement mitigation plans. → Ensure a straightforward escalation process if the risk owner needs help. 5/ Monitor and Update Regularly: → Schedule regular risk reviews and status updates. → Keep an eye on emerging risks and adjust plans as your project evolves. → Maintain an open feedback loop with stakeholders on the evolving risk landscape. → Use project management tools to automate risk tracking and reminders. 6/ Communicate Effectively: → Keep stakeholders informed about risk status and changes. → Be transparent about potential impacts and solutions. → Ensure communication is clear and consistent across all levels of the team. → Adjust your communication style based on your stakeholders' needs and preferences. Managing risk doesn’t have to be complicated. Focus on 𝗶𝗱𝗲𝗻𝘁𝗶𝗳𝘆𝗶𝗻𝗴, 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗶𝗻𝗴, and 𝗮𝗰𝘁𝗶𝗻𝗴 𝗲𝗮𝗿𝗹𝘆; you'll set your project up for success. What’s one risk management tip you live by? Let’s share some wisdom!

📉 4 Biggest Post-Merger Integration Risks 📉 Empirical studies conducted by the Institute for Mergers, Acquisitions, and Alliance drawn from an exhaustive analysis of 45,000 data points reveal interesting insights on M&A post-integration risks. They examined over 300 potential risk factors, applying statistical criteria to identify the core influencers of post-merger risk. They ended up with 35 significant factors which they categorized into four domains. 1️⃣ Synergy Risks > Synergy is the added value when two companies merge, like cost savings and efficiency > If planning or execution falls short, benefits can fade > Inadequate integration of strengths and missed cost-saving chances may lead to setbacks 2️⃣ Structure Risks > Mismatched structures and processes bring confusion, disrupting smooth operations > Departments, teams, and reporting lines need clear coordination; confusion and inefficiency must be minimized 3️⃣ People Risks > Merged employees with diverse cultures and habits can resist change, lowering morale > Effective management is key to minimizing resistance, boosting motivation, and ensuring smooth role transitions 4️⃣ Project Risks > Poor execution, lack of expertise, or resources can lead to delays and cost overruns > A well-managed project with adequate resources is vital for a successful integration Addressing and mitigating these risks is essential as each of these are pivotal points that shape the merger's transformative journey. The image below outlines the factors to keep in mind to minimize their risks.👇🏼 What are some other M&A topics you'd like me to cover? Let me know. 💬 Serial Entrepreneur & Investor Helping Startups Become Unstoppable – David Hauser #entrepreneurship #venturecapital #startup #mergers #acquisitions

Following up on my last post on DPIA/AIA. There are 4 major ways you can respond to discovered risks when you assess answers procured from relevant stakeholders post-completion of a DPIA/AIA Questionnaire. 1. Risk Mitigation: reduce the likelihood/effect of the risk. E.g., on security measures questions, if a stakeholder had answered “Yes, we are going to be using encryption AES-128 standard”, you can suggest AES-256. Yes, 128 has not been cracked but 256 is the standard. Or if encryption is only planned for data-at-rest, you can suggest encryption for data-in-transit as well. 2. Risk Avoidance: substitute the cause/source of the risk totally. If biometric data would be processed to have access to a platform by users and it ordinarily might cause problems — i.e., more compliance requirements (like BIPA), more cost/resources to comply — avoid the risk using biometrics brings by suggesting an alternative, e.g., username and password + MFA. 3. Risk Transference: if a platform or AI system will process customers’ debit/credit card payments, for example. This suggests the additional need to comply with the PCI-DSS. Instead of worrying about this compliance, and still running the risk of liability for breach of payment card data, engage a payment processing company like Stripe (I know, free commercial), and transfer that risk of compliance and any responsibilities for breach, etc, to them via a contract. 4. Risk Acceptance: if the “cost” of preventing a risk would be higher than the “effect” the risk would have — it might make sense to just accept the risk, don’t forget to get a sign-off. It’s not your business as a privacy professional to accept risks. But remember to assess the divergence between quantitative vs. qualitative effects of risks — very crucial.

Me: “What’s your timeline for diligence on this deal?” Client: "Diana, honestly … we need it yesterday." We were brought in pretty late into the deal. I’m always shocked at how quickly M&A can move. So, you don't have time to check everything, you need to prioritize. While every deal is different, here’s a good starting point of where to look: 1) Key executives: Focus on the C-suite for corporate governance issues and key business leads that are crucial to the company's core operations. 2) Business model risks: What could tank this company overnight? Regulatory changes? Tech disruption? Concentrate there. 3) Material partners: Who are the top 3-5 partners (be it customers and/or suppliers) that could cripple operations if they walked? Are there special or privileged relationships that will fall apart after the deal? 4) High-risk locales: If they're operating in known trouble spots, those merit extra attention, especially as it increase bribery/corruption and financial crimes risk. Remember, the goal isn't perfection. Especially under a time crunch. You're not trying to uncover every pebble. You're looking for the boulders that could derail the entire deal. Once you’re comfortable with these risks, you can dig deeper after signing. #mergersandacquisitions #duediligence #riskbasedapproach #investments

Leveraging ISO 42001, ISO 27001, and ISO 22301 for DORA Compliance The Digital Operational Resilience Act (DORA) sets comprehensive requirements for financial entities to ensure ICT system resilience. Three key ISO standards can support DORA compliance: 1. ISO 42001: Artificial Intelligence Management Systems Key clauses supporting DORA: - 4.1 Understanding context: Identifies factors impacting AI systems. - 6.1 Addressing risks and opportunities: Supports AI risk management. - 8.4 AI system impact assessment: Aligns with continuous ICT risk monitoring. These ensure AI systems are robust, secure, and adaptable to threats, supporting DORA's operational resilience mandate. 2. ISO 27001: Information Security Management Systems Relevant clauses: - 6.1.2 Information security risk assessment: Identifies and evaluates risks. - 8.2 Risk assessment and treatment: Details ongoing risk mitigation. - 9.3 Management review: Ensures continuous ISMS improvement. Implementation supports DORA's security and data protection requirements, establishing continuous improvement and compliance. 3. ISO 22301: Business Continuity Management Systems Key clauses: - 8.2 Business impact analysis and risk assessment: Evaluates disruption impacts. - 8.4 Business continuity plans: Ensures comprehensive response strategies. - 9.1 Monitoring and evaluation: Focuses on continuity performance. These help develop continuity plans for operational resilience and recovery, addressing DORA's requirements. Integrating ISO Standards for Comprehensive Compliance: - Unified Risk Management: Combine risk assessments from ISO 42001 and ISO 27001. - Comprehensive Continuity Planning: Use ISO 22301 strategies to support ISO 42001 and ISO 27001 resilience aspects. - Continuous Improvement: Implement feedback loops from all standards for ongoing ICT resilience enhancement. By leveraging these ISO standards, financial entities can create a defensible framework for DORA compliance and reporting. ❗ Note: I've excluded ISO27036 only for sake of brevity, but it should be on your radar as well.❗ If you'd like to discuss, or for help getting started, please reach out! A-LIGN #DORA #ISO42001 #TheBusinessofCompliance #ComplianceAlignedtoYou

Business speaks the language of revenue and reputation. If your risk assessment doesn’t, you’re behind. I think we all agree when I say... If you aren’t reviewing your client’s most critical asset, you’re leaving blind spots that can cost them their business. So, what is your client's most critical asset? a server or some other blinky box with white noise, an endpoint, a database, their data? NO! ->It’s their customer contracts. Why? Your clients sign contracts with their customers filled with data security and privacy provisions, compliance mandates, technical control requirements, vulnerability scanning & reporting obligations, right-to-audit provisions, breach notification timelines, and more. If your assessment skips these contractual promises, you’re failing to measure risk where it matters most to your client -> revenue and reputation. Try this on your next risk assessment… -Sample your client’s top 5 revenue producing contracts, MSAs, or SOWs. -Gap their current practices against the data security, data privacy, and compliance requirements in those agreements. And report findings that show... ...What requirements they agreed to (often without fully understanding). ...Where their processes, technology, and practices don’t meet those requirements. ->Tie remediation costs back to the value of the contracts themselves. When your client sees a roadmap to protect millions in contract value, they’ll immediately understand the real risk to their revenue… Speak their language, shrink risk where it matters most, and you have a client for life that values what you do for them! #ciso #dpo #business #risk

Root Cause Analysis: Driving Continuous Improvement In our current issue of Compliance and Ethics: Ideas & Answers, Rebecca Walker leads us through the practical application of root cause analysis (RCA).  As she explains, “RCA identifies the underlying causes of compliance violations, enabling more effective remediation and program improvement. Without understanding root causes, remediation efforts risk addressing only symptoms, leaving organizations vulnerable to repeat failures.” She demonstrates the very clever technique of the “5 Whys” using an example of a violation by a procurement manager: Why did the procurement manager fail to disclose her ownership interest? → She didn’t believe it was necessary because she wasn’t the final decision-maker on the contract. Why did she believe disclosure was unnecessary? → She misunderstood the company’s conflict of interest policy and assumed it applied only to those with final decision-making authority. Why did she misunderstand the policy? → The conflicts of interest policy and training did not provide clear examples of indirect influence, such as recommending vendors. Why did the training lack clear examples? → The policy and training materials primarily focused on direct financial conflicts and overlooked scenarios involving indirect influence. Why were indirect conflicts not sufficiently addressed in policy and training? → The compliance program’s risk assessment failed to identify gaps in conflict-of-interest disclosures related to supplier relationships. Rebecca even covers how to use data analytics in RCA.  Her article provides a “how to” playbook – exactly what you would expect from an expert like Rebecca. Click here to read more https://lnkd.in/eSeEzenJ