Key takeaways
- The pros and cons of building an in-house analytics solution versus buying a pre-built one.
- Key factors to consider when deciding between building or buying, such as cost, time to market, customisation, resources, and risk.
- How to align the build vs buy decision with your organization's strategic objectives and long-term goals.
What is the build vs buy strategy?
Deciding between building or buying is a pivotal choice for organizations looking to implement new technologies or systems, especially in analytics. This decision-making process involves weighing the benefits of developing an in-house analytics solution (build) against purchasing a ready-made solution from a third-party vendor (buy).
Each approach has its own set of advantages and challenges, and the choice between the two can significantly impact an organization's resources, time to market, and overall business objectives.
Why should you build an analytics solution?
Creating a custom analytics solution can be a strategic choice for effectively utilizing data in decision-making. Here are some reasons why developing your own product analytics might be advantageous compared to purchasing one:
Complete control
Developing your own embedded analytics software offers unparalleled control over the entire development process. You get to decide on every functionality, appearance, and branding element. This in-house approach provides the flexibility to tailor the solution precisely to your requirements, ensuring every aspect aligns perfectly with your specific business needs.
Perfect for small projects
Creating your own embedded analytics solution can be a game-changer, especially for smaller projects with specific needs. Imagine having a tailored data visualization tool that perfectly aligns with your business insights. When your requirements are straightforward, your developers can swiftly craft these solutions, making in-house development not just a viable option, but the best choice for your business.
Integration with existing systems
You can craft a bespoke solution that seamlessly meshes with your existing systems, whether it's your CRM, ERP, or marketing automation platforms.
Why should you buy an analytics solution?
Numerous software companies feel the heat from clients and competitors to supercharge their analytics features. However, they often find themselves strapped for time and resources to build these capabilities from scratch. Here’s why many opt to integrate a third-party solution instead:
More resource for your internal Dev team
Off-the-shelf solutions provide instant functionalities, eliminating the need for lengthy development and testing phases. This allows your organization to focus on its core strengths and strategic objectives rather than diverting resources to software creation. The time and resources saved enable your engineering team to innovate, develop new features, and enhance your product. As a result, you can significantly accelerate your market entry.
Cost efficiency
Crafting a bespoke analytics tool from the ground up requires a hefty initial outlay for development, rigorous testing, and robust infrastructure. On the flip side, ready-made analytics solutions often come with adaptable pricing schemes, such as subscription models, letting you distribute costs over time. This approach can simplify budgeting, keep expenses in check, and showcase a clear return on investment, particularly for small enterprises or those operating on a shoestring budget. Additionally, seasoned vendors harness economies of scale to deliver sophisticated features and capabilities at a fraction of the cost of in-house development.
Unified brand experience
To preserve the essence and prestige of your carefully crafted brand, embracing a white-label software solution is paramount. Imagine your core product and analytics merging effortlessly, creating a harmonious and cohesive brand journey for your users. Every data insight and analytical tool will blend seamlessly, appearing as an organic part of your product's ecosystem. This not only elevates the user experience but also fortifies your brand's identity and credibility.
Availability of training resources and technical support
Opting to purchase provides an abundance of educational materials and technical assistance from the embedded analytics provider. These resources often encompass comprehensive user guides, interactive online tutorials, informative webinars, and prompt customer support services, all aimed at enabling business users to maximize the solution's potential.
This support is especially beneficial for companies with limited technical know-how, as it guarantees that users can fully utilize the embedded analytics solution. Additionally, vendors usually offer customer support to resolve any problems that may occur, ensuring peace of mind and minimizing downtime.
Continuous upkeep and improved analytics capabilities over time
Third-party embedded analytics vendors consistently enhance their products. They invest in research and development to add new features, fix problems, improve user experience, and stay current with industry trends.
This allows you to leverage advanced analytics features without the burden of handling updates on your own. Moreover, vendors typically offer strong customer support to maintain the solution's smooth and efficient operation.
How to decide if build or buy is the best option
When deciding between building or buying an analytics solution, it's essential to weigh the pros and cons of each approach.
Expertise and resources
- Build: Constructing your own embedded analytics tool is viable if your company has a proficient team and substantial resources.
- Buy: Opting for an existing product analytics tool is sensible if your team lacks expertise or if you cannot afford a significant initial investment, allowing swift use of advanced features without overextending resources.
Flexibility to scale
- Build: Achieving effective scalability involves navigating complex architecture, infrastructure, and related environments. Expertise is essential to ensure automated and flexible scalability across data volume, number of users, and cost, all while maintaining performance.
- Buy: By choosing the right embedded analytics platform, you gain the valuable ability to scale on demand, ensuring your system can handle increased demands without compromising performance.
Cost
- Build: Building an in-house solution requires a significant upfront investment in development and ongoing maintenance.
- Buy: Buying a solution involves licensing fees but can reduce development costs and speed up time to market.
Ultimately, the decision between building and buying an analytics solution should align with your organization's strategic objectives, resource availability, and long-term goals.
Key questions to consider in the build vs. buy debate
When faced with the decision to build or buy an analytics solution, it's crucial to ask the right questions to guide your choice.
Organizational needs
- What are the core functionalities you require from an analytics solution?
- Are there unique requirements that off-the-shelf products may not meet?
Resources at your disposal
- Do you have a team of skilled developers, data scientists, and IT professionals who can design, implement, and maintain an in-house solution?
- Can my organization afford ongoing costs related to licensing and support services?
Time to market is another critical factor
- How quickly do you need to deploy an analytics solution?
- Will in-house development stick to timelines?
Risk assessment
- What are the potential risks associated with each approach? Including cost, time and resource.
- Can you find a third-party vendor who you can depend on to deliver your requirements?
Total cost of ownership
- Building an in-house solution may save on licensing fees, but it requires ongoing investment in development, maintenance, and updates. Can my organization keep up with the costs?
- What option will deliver the best return on investment for my organization?
Balancing expectation vs reality
Projects that are built in-house frequently encounter issues due to unforeseen expenses and long-term risks.
For instance, opting to build an application in-house means that your internal team will bear the full responsibility for support, maintenance, enhancements, scaling, and upgrades. If the application gains traction and begins to scale, this success will inevitably lead to increased demand for new features and capabilities. Consequently, this can result in a development backlog and accumulating technical debt. It's worth noting that, according to TeamStage, 70% of projects fail to meet their original goals, often due to such challenges, according to recent project management statistics.
This is why taking the time to make sure you have addressed key business requirements outside of basic features and functionality is critical for building a successful product and business.
Choosing to buy
At Panintelligence, we ensure a seamless experience, eliminating any potential obstacles in your data analytics journey. Our solution requires minimal coding, making the development process both quick and straightforward. This allows customers to visualize extensive datasets effortlessly, without needing any technical expertise.
Choosing Panintelligence as your third-party analytics vendor means you can focus your development resources on enhancing your core applications, all while accelerating your business growth. Our powerful pi platform operates efficiently in the background, providing you with reliable and insightful data analytics.
Conclusion
Choosing whether to build or buy an analytics solution is a pivotal and intricate decision that can greatly affect your organization's efficiency, expenses, and strategic aims. Each option has its own set of benefits and drawbacks, and the best choice hinges on a comprehensive assessment of your unique requirements, resources, and long-term plans.
The decision should ultimately be in harmony with your organization's strategic goals, resource availability, and future objectives. By meticulously evaluating the advantages and disadvantages of each option and taking into account factors like cost, time to market, customization, resources, and risk, you can make a well-informed choice that optimizes your return on investment and meets your business needs.
