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Why Problem Solving Fails: Using a Post-Mortem Review

Using a Post-Mortem Review to Learn from Mistakes and Move Forward Without Blame

In the fast-paced world of problem solving, it’s easy to feel like we’re on a constant treadmill of trial and error. Despite our best intentions and efforts, some strategies may flop spectacularly, leaving us feeling disheartened and questioning our skills. But what if there was a way to turn our failures into valuable lessons? Enter the post-mortem review—a structured approach to reflect on failed attempts, learn from our mistakes, and move forward free from blame.

Understanding the Post-Mortem Review

A post-mortem review is often used in various fields, including project management and software development, to analyse what went wrong after a project or initiative fails. However, this practice can be beneficial in any realm that requires problem solving. The aim is not to point fingers but to foster a culture of openness and learning.

Here’s how you can conduct a lightweight post-mortem review:

1. Gather Key Players

First, assemble everyone involved in the problem-solving process. This includes team members, stakeholders, and anyone affected by the issue. Ensure that the environment feels safe and open; emphasise that the goal is collective learning, not assigning blame.

2. Define the Objective Clearly

Outline the specific problem or challenge that was addressed and why it mattered. This establishes context for participants as you dissect the failure and sets a collaborative tone for the discussion.

3. Chronicle the Attempt

Discuss the steps taken to solve the problem. What strategies were employed? What resources were allocated? Ensure that everyone contributes their perspective. Recording these details provides a clear timeline of events, helping to identify where things diverged from the expected outcome.

4. Identify What Went Wrong

This is arguably the most crucial part of the process. Encourage an open dialogue about what didn’t work and why. Focus on factors such as:

Miscommunication: Were there misunderstandings in roles or expectations?
Resource Allocation: Did you have the necessary tools or budget?
Timing: Was the timing off with regards to project deadlines and market needs?
Assumptions: Were there any key assumptions that proved incorrect?

By pinpointing these areas, you can differentiate between systemic flaws and individual missteps, steering the conversation away from blame.

5. Extract Lessons Learned

Now comes the exciting part: transforming failures into actionable insights! Ask participants what they learned and how similar mistakes can be avoided in the future. For example:

Could better communication channels prevent misunderstandings?
Should the team conduct more thorough research before implementing solutions?
Would revisiting the criteria for success prior to launching ideas make a difference?

Document these lessons, as they will serve as a valuable reference for future initiatives.

6. Create a Forward-Looking Action Plan

Finally, develop a proactive strategy based on your findings. This could include:

Implementing regular check-ins to ensure alignment amongst team members.
Allocating time for team training or workshops on communication skills.
Creating a shared document that outlines core assumptions and decision-making processes for future projects.

7. Cultivate a Culture of Continuous Improvement

Consider making post-mortem reviews a standard practice within your organisation. When employees understand that failures are simply stepping stones to growth, they become more willing to take calculated risks. Reinforce the idea that learning is a continual journey, one that requires reflection and honesty without fear of repercussions.

Conclusion

The truth is, failure is an inherent part of any problem-solving process. Instead of allowing it to lead to frustration or defensiveness, embrace the opportunity to learn and grow. By utilising a structured post-mortem review, you can transform past mistakes into stepping stones towards future success. Remember, it’s not just about solving the problems at hand—it’s about cultivating an environment where every setback becomes a lesson learned, paving the way for innovation and progress.

So, gather your team, ask the tough questions, and start turning those flops into triumphs!

Feature Problem solving

Mastering Problem Solving: How to ask better questions…

Mastering Problem Solving: How to Ask Better Questions Using Socratic Questioning, Appreciative Inquiry, and Challenge Mapping

In today’s fast-paced world, the ability to solve problems efficiently and effectively can make or break teams and organisations. But what often goes overlooked is the pivotal role that asking the right questions plays in problem-solving. Getting to the heart of an issue starts with good questioning. This article explores three powerful techniques—Socratic questioning, appreciative inquiry, and challenge mapping—that can enhance how individuals and teams understand and frame their challenges.

The Art of Socratic Questioning

Named after the ancient Greek philosopher Socrates, this technique promotes critical thinking through dialogue. Rather than providing answers or solutions, Socratic questioning encourages individuals to reflect deeply on their assumptions and thought processes. Here’s how you can implement it:

Clarify your thoughts: Begin by asking, “What do I really mean by this?” or “Can you explain that further?”
Challenge assumptions: Question the premises underlying a belief. Use queries like “What are we assuming here?” or “How do we know this is true?”
Explore implications: Encourage exploration of the consequences of a perspective by asking, “What might happen if we pursue this course of action?”
Seek alternatives: Motivate creative thinking with questions such as “What are other ways to approach this issue?” or “What might someone with an opposing view say?”

By fostering a culture of inquiry, teams can surface hidden assumptions and encourage deeper understanding of the issues at hand.

Appreciative Inquiry: Focusing on What Works

While traditional problem-solving often zeroes in on problems and deficits, appreciative inquiry flips that perspective by seeking out strengths and successes. This technique hinges on the idea that asking positive questions can generate constructive insights and foster collaboration. Here’s how to apply appreciative inquiry in your team:

Identify the best moments: Begin by asking team members, “When have we succeeded in overcoming challenges in the past?”
Discover what works: Encourage discussions around strengths with questions like “What are our key competencies?” or “What has brought us joy in our work?”
Dream about possibilities: Invite team members to envision an ideal future by asking, “What would success look like for our team?” or “If we could create the perfect solution, what would it entail?”
Design your path forward: Finally, formulate actionable steps by asking, “What can we do to replicate our successes?”

Using appreciative inquiry not only inspires positivity and motivation but also equips teams with a broad understanding of their core strengths.

Challenge Mapping: Visualising Problems

Challenge mapping is a visual and strategic way of breaking down complex problems into manageable components. This technique helps teams organise their thoughts and identify key areas for improvement. Here’s how to utilise challenge mapping effectively:

Define the challenge: Start by clearly stating the problem at the centre of your map.
Identify key factors: Branch out from the central challenge to highlight contributing factors or stakeholders involved in the problem.
Create actionable paths: For each factor, brainstorm potential solutions or approaches. Map these out visually to see connections and relationships between different elements.
Prioritise actions: Finally, assess which solutions are the most feasible or impactful and label them according to urgency or importance.

This method not only clarifies the complexity of a problem but also prompts teams to think critically and collaboratively about potential solutions.

Bringing It All Together

Mastering problem-solving through effective questioning techniques can significantly enhance team dynamics and outcomes. By incorporating Socratic questioning, appreciative inquiry, and challenge mapping into your problem-solving process, you can create a culture where thoughtful dialogue and innovation thrive.

Practical Action Steps:

Start a weekly questioning session: Dedicate some time each week to practice Socratic questioning with your team on current challenges.
Conduct an appreciative inquiry workshop: Organise a session focusing on past successes to inspire optimism and engagement within the team.
Utilise challenge mapping in project planning: Implement challenge mapping in your next project meeting to clarify issues and generate actionable solutions.

By weaving these techniques into your problem-solving toolkit, you empower yourself and your team to tackle challenges more effectively and creatively. Remember, great problem-solving starts with great questions. Happy questioning!

Problem examples Feature Problem solving

The Case of the Declining Newsletter Engagement

Background: A B2B SaaS provider relied heavily on email marketing to nurture leads and retain customers. Their weekly newsletter shared case studies, feature updates, and opinion pieces. Over a six-month period, email open rates dropped by half and click-throughs declined even more. Feedback was minimal, and marketing ROI fell off a cliff.

Workaround

The marketing team tried increasing frequency—sending multiple campaigns per week, experimenting with send times, and tweaking subject lines. They also ran one-off promotions to re-engage users. However, these efforts only resulted in increased unsubscribe rates and flagged emails.

Symptom: Open and click-through rates were steadily declining. Engagement was down and complaints were up.
Workaround applied: More frequent, more aggressive emailing.

Deeper Analysis

A review of email data showed no segmentation in the audience list. Long-time customers, new sign-ups, and trial users all received the same generic newsletter. Many emails were flagged by spam filters due to lack of authentication protocols and poor domain reputation. Feedback surveys revealed the content wasn’t relevant or timely.

Cause: Poor audience segmentation and deliverability issues.

Root Cause

An outdated CRM with basic mailing list functionality and no clear owner of email performance KPIs. Content planning was done reactively, based on internal priorities, not audience needs.

Root Cause: No clear owner of KPI measures, no audience need research t drive content planning and an out of date CRM with poor functionality – a perfect storm!

Solution

They moved to a modern marketing automation platform with smart segmentation and behavioural triggers. The team reworked their content calendar around user journeys and implemented proper email authentication (SPF, DKIM, DMARC).

Solution: New content calendar based on user journeys and a new modern marketing automation platform with segmentation.

Outcome

Within two months, open rates rose 45%, and user feedback became positive. New leads received tailored onboarding content, while long-term customers were offered relevant product tips and advanced usage guides. Engagement and pipeline value rebounded.

Problem examples Feature

The Case of the Inaccurate Inventory

Background: A regional online retailer experienced frequent disruptions due to incorrect stock records. Products listed as available would turn out to be out of stock when pickers arrived at the shelves, leading to delayed shipments, cancelled orders, and dissatisfied customers. The issue worsened during promotional periods and seasonal peaks.

Workaround

To prevent order errors, warehouse supervisors instituted daily manual counts for top-selling items. Staff used spreadsheets to log counts and reconcile discrepancies each morning before operations began. This temporary fix created new problems: increased workload, delays in order processing, and stress among floor staff.

Symptom: Frequent fulfilment errors and a spike in customer service complaints.
Workaround applied: Manual daily recounting of popular SKUs.

Deeper Analysis

The root of the issue wasn’t human error, but system design. The inventory management software updated stock levels in batches overnight, and it wasn’t connected to the ecommerce platform in real time. As a result, stock shown online didn’t match physical inventory. Discrepancies compounded daily.

Cause: A disconnect between sales and inventory systems, with no live syncing.

Root Cause

Technology and process had not kept pace with changing workplace behaviours. The company had no visibility over how spaces were actually used, nor any consequences for hoarding or misusing shared resources.

Root Cause: The company had grown quickly and patched its operations with separate tools. Integration and automation were sacrificed for speed. Inventory logic had not been reviewed since the company was much smaller.

Solution

They adopted a cloud-based ERP solution that integrated sales, inventory, and warehouse management. The system updated stock levels in real time and included handheld scanner integration for immediate adjustments during picking. Inventory accuracy was audited weekly to improve discipline.

Solution: the organisation adopted a cloud-based ERP solution that updated stock levels in real-time.

Outcome

Order accuracy improved dramatically. Customer complaints reduced by over 60%, and warehouse efficiency improved as manual tasks were phased out. Seasonal peaks were handled without overtime or errors.

Feature

Use AI to fix Failure Demand

Failure demand is, in essence, the additional (and unnecessary) workload created when an organisation fails to provide a product or service accurately or completely at the first point of contact. In large citizen-facing organisations—government agencies, healthcare systems, or large federated enterprises—failure demand often arises from structural and procedural issues that, if left unmanaged, create spirals of repeated contacts, rework, complaints, and escalations.

Below are common causes of failure demand in large federated organisations, along with ways in which AI can help alleviate or prevent these issues.

1. Fragmented Information and Siloed Systems

Cause:

• Multiple disconnected databases or information systems mean that staff can’t easily access the correct, up-to-date information about a citizen or case.

• Different departments or agencies have their own processes, making it difficult to get a single, integrated view.

How AI Helps:

1. Data Integration & Master Data Management

• AI-driven data integration or entity resolution can match and merge records across siloed systems, providing a single source of truth.

2. Knowledge Graphs

• These can unify information from various internal and external systems, surfacing the relevant data to the front line or self-service portals in real time.

2. Repeated or Escalated Inquiries

Cause:

• Citizens have to call multiple times or contact different departments because they never receive the correct answer or a complete resolution on the first attempt.

• Instructions or next steps are unclear, requiring additional clarifications.

How AI Helps:

1. Natural Language Processing (NLP) for Triage

• AI-based chatbots and virtual assistants can quickly assess the request and route it to the correct team, reducing misrouted calls.

2. Automated Knowledge Bases

• AI can suggest the next best action or provide consistent answers to common questions, reducing inaccurate or incomplete information.

3. Lack of Process Visibility (for Both Staff and Citizens)

Cause:

• Citizens have little visibility into the status of their application, request, or case.

• Staff themselves may struggle to track cases as they move through different departments, leading to delays and confusion.

How AI Helps:

1. Predictive Tracking and Alerts

• AI can monitor case progress and send automatic notifications to both citizens and staff about status changes, required documents, or impending deadlines.

2. Process Mining and Workflow Optimisation

• AI-driven process mining tools analyse workflow logs to identify bottlenecks or high-friction steps, prompting proactive solutions.

4. Overly Complex or Confusing Service Design

Cause:

• Citizens are forced to navigate confusing online portals, physical forms, and long instructions, which leads to errors or incomplete submissions.

• Lack of standardisation across departments can create additional steps and inconsistencies.

How AI Helps:

1. Personalised Digital Assistants

• Virtual agents that guide citizens step-by-step, ensuring forms and data are filled correctly and explaining next steps in simple language.

2. Adaptive User Interfaces

• AI can tailor the user experience based on the user’s profile, automatically simplifying the path or adjusting the language for clarity.

5. Inconsistent Communication or Messaging

Cause:

• Different channels (phone, email, web chat, social media) give conflicting information or instructions.

• Citizens receive either no response or delayed responses, leading to additional follow-ups.

How AI Helps:

1. Omni-channel Response Orchestration

• AI models can be trained on policy guidelines and knowledge bases to ensure consistent, channel-agnostic responses.

2. Sentiment Analysis and Real-time Alerts

• Monitoring digital communications can quickly highlight negative or confused user sentiments, prompting staff to intervene before citizens need to escalate.

6. Manual, Repetitive Tasks Leading to Errors

Cause:

• Staff spend time on repetitive data entry and manual verification processes, which are prone to human error.

• A single mistake can lead to multiple follow-up calls and corrective work.

How AI Helps:

1. Optical Character Recognition (OCR) and Automated Data Entry

• AI tools can accurately parse large volumes of forms, extracting data and populating systems automatically.

2. Robotic Process Automation (RPA)

• Combining RPA with AI (“Intelligent Automation”) can handle repetitive workflows, flags issues automatically, and hand off only exceptions to human staff.

7. Limited Staff Training or High Staff Turnover

Cause:

• In large federated organisations, staff turnover can be high, or training may be inconsistent.

• Knowledge retention is poor, meaning new or rotating staff do not always have the expertise to handle calls correctly.

How AI Helps:

1. Real-time Call Guidance

• AI-driven recommendations can guide agents during phone or chat interactions, suggesting answers based on historical successful interactions.

2. Machine Learning for Training Gaps

• Analysis of interactions can highlight patterns of agent errors or knowledge gaps, guiding targeted staff training efforts.

8. Reactive Instead of Proactive Approach

Cause:

• Processes are often designed to react to incoming inquiries rather than preventing confusion or mistakes in the first place.

• Citizens only discover requirements (e.g., missing documents, extra steps) after they have already submitted something incorrectly.

How AI Helps:

1. Predictive Analytics

• By analysing historical data, AI can forecast which cases might lead to repeated follow-ups or escalate, prompting proactive outreach.

2. Proactive Communication

• Automated notifications (e.g., reminders, deadline notices) reduce the likelihood of citizens missing requirements and calling back to ask for clarifications.

9. Inability to Identify Root Causes

Cause:

• Without an organised way to analyse large volumes of calls, emails, and visits, it is difficult to understand why so many follow-ups or escalations happen.

• Root-cause analysis often requires manual effort, which is time-consuming and prone to oversight.

How AI Helps:

1. Text and Speech Analytics

• AI can analyse phone transcripts, chat logs, and emails to uncover themes, common queries, or shared blockers driving repeat contacts.

2. Topic Clustering

• AI clustering techniques group citizen complaints or issues, helping leadership see broader trends and attack the underlying causes.

10. Poor Feedback Loops Between Front-Line and Policy/Process Owners

Cause:

• Front-line staff and citizens encounter the same problems repeatedly, but those issues are not effectively communicated upstream to the departments that design the processes.

• This results in short-term fixes (workarounds) rather than systemic changes (resolutions to root causes).

How AI Helps:

1. Closed-Loop Feedback Systems

• AI-driven dashboards can aggregate real-time data on contact types, resolutions, and user satisfaction, automatically flagging major process issues.

2. Continuous Improvement Recommendations

• Machine Learning (ML) algorithms can recommend policy or process changes based on patterns and outcomes, pushing insights directly to policy owners.

Key Takeaways

1. Integration and Data Sharing

• Breaking down organisational silos is essential to reducing failure demand. AI can help by unifying and analysing disparate data.

2. Personalisation and Proactivity

• AI can provide personalised guidance and proactively alert citizens (and staff) to potential issues, cutting down on repeated contacts.

3. Automation of Low-Level Tasks

• Robotic Process Automation (RPA) and intelligent document processing reduce human error and free staff for more complex, value-adding activities.

4. Insight Generation

• Text analytics, speech analytics, and clustering methods can reveal hidden causes of frequent failures and drive continuous improvement.

By applying AI methods to target these root causes—fragmented data, repeated inquiries, manual errors, and slow feedback loops—large citizen-facing and federated organisations can decrease failure demand, improve citizen experiences, and allow staff to focus on more valuable, mission-critical tasks.