Week 44 - Mastering the '🚧 Build vs. 🛒Buy' Conundrum: A Comprehensive Guide for Product Managers
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“The 'build vs. buy' decision is not just about cost or capabilities. It's a strategic choice that shapes the future of your product, impacts your competitive positioning, and ultimately, defines your ability to serve your customers effectively.”
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💯 Framework // Concept // Mental Model
Every product manager is tasked with making significant decisions that shape the product's development trajectory, sustainability, and market success. Among these choices, the 'build vs. buy' decision 🚧 vs. 🛒 stands as a critical turning point that can significantly impact the product's lifecycle, budget, and future growth.
Product managers often juggle between building a custom solution in-house or buying a ready-made solution available in the market. This decision carries significant implications for time-to-market, resource allocation, cost, and competitive advantage.
Understanding the Build vs. Buy Decision 🤔
Build 🛠️
Building involves creating a custom solution from scratch. Let's consider Netflix, for instance. Instead of relying on an existing content delivery network (CDN), Netflix decided to build its own CDN, Open Connect, allowing them to control the distribution and streaming quality of its content.
Buy 💳
Buying involves acquiring a pre-built software solution from a third-party vendor. A prime example is Slack, a widely-used communication tool that most companies prefer to buy rather than create a similar tool from scratch.
Factors Influencing the Build vs. Buy Decision 🧐
Budget and Resource Constraints 💰
Building software in-house can be expensive, but it may offer a long-term return on investment. Amazon's decision to build Amazon Web Services (AWS) in-house is another prime example. Initially, AWS was created to handle Amazon's own retail application workloads. But seeing the potential, they invested heavily in developing it further. Despite the huge costs involved in developing and maintaining the cloud infrastructure, AWS has not only provided Amazon with a reliable and scalable solution for their own services but has also grown into a significant profit-making business itself. Amazon has successfully sold these services to other businesses globally, leading to a new revenue stream that now accounts for a large part of Amazon's profit.
Time-to-Market ⏱️
Buying generally enables faster deployment. Zoom is an example of a ready-made video conferencing tool that companies adopt quickly rather than building a similar tool in-house.
Unique Requirements 🎨
If the product requires highly specialized features, building may be the best option. Tesla, for example, builds its software and hardware in-house to meet its unique requirements.
Competitive Advantage ⚔️
Building might make sense if the software will form a significant part of the business's unique value proposition, just like Amazon's recommendation engine which was developed in-house.
Control and Security 🔒
Building in-house allows complete control over the product. Apple, for instance, is known for its strict control over both hardware and software, enabling it to offer top-tier security.
The Hybrid Approach 🔄 (Check out the Templates at the end of the Newsletter)
This approach involves buying off-the-shelf components for non-core operations and building custom elements for strategic differentiators. Dropbox is an excellent example, as it started with Amazon Web Services (AWS) for storage and then gradually built its infrastructure.
A Decision-Making Framework for Product Managers 🗺️
Define Product Requirements 📝: Start by understanding what the product needs to achieve.
Evaluate Available Solutions 🔍: Research existing solutions in the market that meet your requirements.
Assess In-House Capabilities 🏠: Evaluate your team's skills, resources, and capacity.
Cost-Benefit Analysis 💹: Compare the cost of building vs. buying.
Risk Assessment 🎲: Consider the risks associated with both options.
Let’s do this by taking a hypothetical example
MedHealth Inc. 🏥, an emerging startup in the health-tech industry, plans to launch an application that leverages AI to provide personalized health recommendations for users based on their fitness data.
To build this AI-driven fitness application, the product manager, Jason, is faced with the challenging 'build vs. buy' decision. Jason knows that both choices have their strengths and weaknesses.
Define Product Requirements 📝:
Objective: Understand what the product needs to achieve.
Scenario: MedHealth Inc. wants to launch an AI-driven fitness application that provides personalized health recommendations based on user's fitness data.
Excel Template:
Evaluate Available Solutions 🔍:
Objective: Research existing solutions in the market that meet your requirements.
Scenario: Jason identifies a third-party AI engine that can be integrated into the app. It's capable, and secure, but less customized.
Excel Template:
Assess In-House Capabilities 🏠:
Objective: Evaluate your team's skills, resources, and capacity.
Scenario: Jason's team doesn't have skilled AI developers, so building the AI engine in-house would require additional hiring.
Excel Template:
Cost-Benefit Analysis 💹:
Objective: Compare the cost of building vs. buying.
Scenario: Building the AI engine would be costly and time-consuming but would offer complete control and a competitive edge. Buying offers a faster time-to-market but would mean less customization and reliance on a third-party vendor.
Excel Template:
Risk Assessment 🎲:
Objective: Consider the risks associated with both options.
Scenario: Building carries the risk of delay and cost overrun, but allows control over data. Buying has the risk of vendor dependence and less control over the product's core functionality.
Excel Template:
The Build Scenario 🛠️
Jason evaluates the 'build' scenario. Given that the app's unique selling proposition (USP) is providing personalized fitness recommendations, Jason understands that owning the proprietary AI engine could give MedHealth a significant competitive edge. Moreover, this would ensure complete control over data, which is crucial given the sensitive nature of health-related data.
However, building the AI engine would require hiring a team of skilled AI developers, which could be costly and time-consuming. Furthermore, the development process would likely take a year, pushing back the product's launch and possibly allowing competitors to fill the gap.
The Buy Scenario 💳
The 'buy' scenario, on the other hand, offers a faster time-to-market. Jason identifies a third-party AI engine that could be integrated into their app. The engine is capable and secure, albeit less customized to their specific needs.
Buying would free up the company's resources and allow them to focus more on the user interface, marketing, and other business aspects. However, they would be dependent on the third-party vendor for maintenance and updates. Furthermore, recurring licensing fees would increase the product's operational cost.
The Decision 🤔
After analyzing the company's capabilities, budget, time constraints, and market competition, Jason leans towards a hybrid approach. He decides to buy the third-party AI engine for an MVP (Minimum Viable Product) launch to enter the market quickly and validate the concept.
In parallel, he begins building an in-house AI team to develop a proprietary AI engine, which will be integrated into the app in the future iterations once it's ready. This approach allows MedHealth Inc. to swiftly launch the product while also working towards a more competitive, independent solution.
This scenario illustrates how the 'build vs. buy' decision should take into account multiple factors, and how a hybrid approach can often leverage the strengths of both options. 🎯
Conclusion 🏁
The build vs. buy decision is a complex one, involving an analysis of financial, strategic, and operational factors. There's no one-size-fits-all answer. However, by understanding the implications of each choice and applying a systematic decision-making process, product managers can navigate this challenging decision with confidence and clarity.
Remember, the ultimate goal is to deliver value to your users and align with your organization's strategic objectives. So, whether you choose to build, buy, or opt for a hybrid approach, make sure it serves these key priorities. 👍
👇 Click below to get the Template - A Decision-Making Framework for Product Managers 🗺️
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So aptly put 👏