Step 3: Specify the Minimum Viable Product (MVP)

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Having identified the high-impact domain in Step 2, the next step is to break down this domain into potentially valuable ROI use-cases. This approach allows you to deliver tangible value quickly by targeting specific challenges within the domain that can be addressed effectively with available resources. A well-defined MVP also sets a solid foundation for introducing more sophisticated capabilities—such as advanced analytics or AI-driven insights—once the initial data frameworks are established.

Deep Dive into the Selected Domain

Begin by conducting a thorough analysis of the chosen domain to understand its internal structure, processes, and pain points in greater detail:

Map out key processes, workflows, and activities within the domain. Including inputs, outputs, and dependencies for each process.
Gather insights on critical issues, bottlenecks, and areas ripe for improvement from the domain experts.
Get a clear understanding of how data is generated, processed, and utilized within the domain. And identify data sources, data quality issues, and data accessibility challenges.

To guide a deep dive into the selected domain effectively, consider the following questions for in-depth analysis:

Understanding Goals and Objectives:
- What are the core objectives and KPIs of the current domain?
- Which processes contribute most significantly to achieving these objectives?
Processes and Workflows:
- Can you walk me through the key processes and workflows in your domain?
- What are the critical touch points in these processes where data plays a significant role?
- Are there any redundancies or inefficiencies in current workflows?
Pain Points and Challenges:
- What are the biggest challenges or bottlenecks you experience in your daily operations?
- Where do you encounter delays or breakdowns in data flow or process execution?
Data Utilization and Flows:
- How is data currently collected, processed, and used within your domain?
- What tools or platforms are used to support data-driven activities?
- Where do you face data quality issues, and what are the main data accuracy concerns?
Opportunities for Improvement:
- Are there any specific areas where improved data access or automation could streamline operations?
- What types of insights or reports would make decision-making more efficient?
- Are there any emerging trends or technologies you believe could impact your domain positively?
Evaluating Impact:
- What quantifiable improvements do you expect if the identified challenges are resolved?
- How would addressing these data challenges change your strategic or operational outlook in the next year?

Identify High-Impact Use Cases

Within the domain, pinpoint specific use cases or problems that, when addressed, will yield significant benefits. Prioritize these use cases based on their potential impact and feasibility.

For business impact consider whether solving this problem lead to cost savings, revenue growth, or improved efficiency.

Consider the feasibility of addressing problems. Can the issue be addressed with the available data and technology? Is it possible to implement a solution within a reasonable timeframe?

Another important consideration is the requirement of stakeholder support. Consider whether key stakeholders recognize the importance of this problem, and whether there is buy-in from those who will be affected by the change. Your key stakeholders are critical for user adoption and change management. Any new tool will be met with some resistant, if key stakeholders are not involved organizational buy in is destined to fail.

Define the Minimum Viable Product (MVP)

An MVP is a solution that addresses the core needs of the selected use case with minimal resources and time investment. The goal is to deliver value quickly, validate assumptions, and gather feedback for future iterations.

Steps to Defining the MVP:

Step 1: Identify your key stakeholders, specifically blockers and champions. Use champions to drive business buy in and adoption. Listen to blockers concerns objectively and use it to refine the solution.
Step 2: Set clear objectives of what the MVP aims to achieve. Establish measurable success criteria and Key Performance Indicators (KPIs).
Step 3: Scope the MVP appropriately by focusing on essential features and functionalities that solve the primary problem. Avoid scope creep by excluding non-critical elements.
Step 4: Plan for quick implementation by leveraging existing tools and technologies where possible. And ensure that the MVP can be developed and deployed within a short timeframe (e.g., weeks rather than months).
Step 5: Quantify the value by outlining the expected value that the MVP will deliver (e.g., potential revenue impact, time savings, cost reduction). Use estimates or data to back up the value proposition to ensure clear stakeholder understanding and alignment. It paved the way for even more advanced optimizations down the line utilizing AI and machine modelling to schedule the plant more effectively.

Once you’ve defined the MVP, move on to Step 4: Execute Minimum Viable Product (MVP) Implementation and Iterate.

Get Your MVP Right the First Time

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🟢 Step 3 in Action

Here’s how this looked at a mid-sized dairy product manufacturing company:

Deep Dive into the Selected Domain:

At a mid-sized dairy product manufacturing company, the Chief Data Officer (CDO) identified supply and logistics as the domain with the highest potential return on a data initiative. The decision to focus on this domain was driven by the high stakes of operational efficiency and the potential for significant cost savings. Within this domain, they broke down processes into key sections and reports, analyzing where impactful changes could be made.

Identify High-Impact Use Case:

OEE (Overall Equipment Effectiveness) was chosen as the focus because it is a comprehensive metric that encapsulates three critical elements of production performance: availability, performance, and quality. Improving OEE can directly lead to reduced downtime, increased throughput, and better product quality—key drivers for operational efficiency. The CDO recognized that by targeting OEE, the company could address bottlenecks that had downstream impacts on production speed and cost. Having the CDO engaged and part of driving the project led to an understanding on the floor which led to day to day usage of new solution.

Defining the MVP:

Objective:The MVP aimed to provide a clear, actionable report that tracked and analyzed OEE, enabling quick identification and rectification of inefficiencies in the production process for each line and machine on the line.
Plan for Quick Implementation:
1. Tools and Technologies Used:The company leveraged existing data infrastructure and analytics platforms to develop the OEE report. Tools such as Power BI for data visualization software and ETL (Extract, Transform, Load) solutions were used for quick data extraction and dashboard creation.
2. Implementation Timeline:The focus was on rapid development and deployment, with a target timeframe of a few weeks to build a prototype that included essential OEE tracking features.
KPIs and Success Criteria:
1. Key Metrics Tracked:Availability (the percentage of scheduled time the equipment is operational), performance (the speed at which the equipment runs as a percentage of its designed speed), and quality (the proportion of good units produced versus the total units).
2. KPIs:Achieving an improvement in OEE within the first quarter after the MVP launch, reducing equipment downtime, and increasing production throughput.
Quantifying the Value:
1. The potential value was quantified by calculating estimated savings from an improvement in OEE, such as reduced operational costs and increased production volume. These metrics were translated into financial projections, showing potential annual cost savings in the millions.
2. The MVP also highlighted how process improvements could contribute to better supply chain predictability and customer satisfaction.

⚠️ Common Obstacles & How to Overcome Them

Concern	Solution
Difficulty Narrowing Down Use Cases	Start with one high-impact metric (e.g., OEE) and refine scope over time.
Attempting Perfection Before Launch	Set a short timeline, prioritize core features, improve after initial feedback.
Stakeholder Skepticism About Scope	Emphasize that the MVP is a stepping stone; showcase quick wins early.
Lack of Clear Success Metrics	Define KPIs at the outset so progress and impact are easy to measure.

Prevent Scope Creep and Complexity From the Start

Want a straightforward, effective MVP? Schedule a free 30-minute call, and we’ll help you outline a clear path to a lean MVP that proves its worth quickly.