Data science and technology alone cannot guarantee product success
There’s a misconception that simply having the latest data science tools and technologies automatically guarantees success. But, as we know, that’s not how the world works. Even the best technology can fall flat without the right context and alignment with the rest of the business.
One of the biggest issues today is the disconnect between tech and commercial teams. Technical teams, often isolated and focused purely on data science or AI, may develop innovative solutions without fully understanding the needs, goals, and workflows of the business. When this happens, the product fails to serve its real purpose, addressing customer pain points or driving business growth. In fact, a staggering number of data science projects never make it past the testing or prototype stages simply because they aren’t aligned with commercial realities.
This problem wasn’t always a concern. In the early days of AI and big data, there was a rush to invest in technology, with less emphasis on how that technology directly impacted business results. Investors were more focused on demonstrating that companies were leveraging the latest tech, rather than on actual outcomes. But as tech continues to mature, and as companies increasingly seek to understand their ROI, it’s becoming clear: investment in technology must be justified by tangible, measurable results. Technology needs to support the commercial objectives and be directly tied to the bottom line.
The expansion of data technology
The last decade has brought about major shifts in how data is handled and integrated within companies. The biggest shift has been the move from siloed data systems to centralized data architectures that provide clearer insights into how different parts of the business interact. Centralized systems allow commercial teams to understand how their actions affect different departments and, vice versa, making it easier to spot bottlenecks and areas of opportunity.
What’s more, tech teams are no longer operating in isolation. They’ve gone from being a support function, called in when needed, to being an integral part of the decision-making process. The result is a much richer, more informed dialogue between technical and commercial teams. When sitting at the table with commercial colleagues, technology teams can understand exactly what the business needs, and how their work can help move the needle.
This change has also led to more effective collaboration and motivated teams. When the tech department understands that their work directly impacts business outcomes, it’s a powerful motivator. They see the value of their contributions, which in turn boosts productivity. This collaboration is key to driving innovation, and it’s one of the reasons companies with integrated teams are outperforming others in today’s competitive market.
Lean-value methodology maximizes efficiency ROI
You’ve likely heard about various project management frameworks, but the lean-value methodology is one of the most practical, especially when your tech investments are under scrutiny. Lean-value focuses on prioritizing the tasks that are most likely to drive value. For tech teams, this means honing in on research or features that will make the biggest impact on achieving company objectives.
What’s important here is the focus on building a minimum viable product (MVP) rather than perfecting every little detail from the start. Early perfectionism can delay projects, wasting valuable resources. Instead, lean-value emphasizes getting something usable out quickly and iterating on it based on real-world feedback. This results in faster rollouts, less waste, and more valuable products.
Regular reviews of progress and objectives keep teams on track. When things get off course, they’re reassessed, and non-essential tasks are deprioritized. It’s also a more inclusive process for neurodiverse team members because the framework offers a clear, structured approach to stay focused on the goal without unnecessary distractions.
Lean-value approach
The lean-value mindset extends to the way we handle data architecture. Traditional data warehouses have long been the go-to solution for storing and processing data, but they come with their own set of problems. They’re rigid, expensive, and struggle to handle unstructured data. For modern businesses, data needs to be flexible and adaptable. That’s where data lakehouses come in.
A data lakehouse merges the best of data lakes and warehouses, allowing for a unified system that manages both structured and unstructured data more efficiently. In combining lakehouses with large language models (LLMs), businesses can process vast amounts of data much faster and at a lower cost. The integration of AI further accelerates this process, cutting down on time-to-insight and maximizing ROI.
While the benefits are clear, businesses need to exercise caution. Data governance remains a top priority, keeping data secure, accurate, and compliant is non-negotiable. The more complex the data architecture, the more important it becomes to maintain comprehensive systems to monitor and optimize performance. In balancing performance and cost, businesses can ensure they’re getting the most value out of their data architecture.
Key takeaways
Gone are the days when tech teams were viewed as a back-office function. They’re expected to directly impact revenue, just like sales or marketing. The key to this shift is the lean-value methodology, which makes sure that technology teams are delivering measurable value that ties directly to business outcomes.
The integration of lean-value into both product development and data architecture has empowered tech teams to drive revenue growth. When seeing the direct impact of their work on the company’s bottom line, tech teams are motivated to push forward with more innovative solutions. Visibility into outcomes has improved how tech departments are viewed within the organization.
What this all comes down to is that technology has to be a driver of business success. When the work of technology teams aligns with business objectives, the entire company benefits. High-performing teams are motivated, companies see measurable returns on their tech investments, and the organization as a whole is positioned for sustainable growth.
