Making Strategic Decisions: Small Improvements vs. Redesigning Digital Products

Making Strategic Decisions: Small Improvements vs. Redesigning Digital Products
Photo by Riho Kroll / Unsplash

Product strategy isn't easy. Product and digital leaders face critical decisions about investing in their digital products. Determining whether to make small improvements or undertake a full redesign or rebuild requires evaluation.

I wrote this post to explore the key factors leaders should consider, the challenges associated with each factor, and strategies to mitigate these challenges during the decision-making process.

Insights from the voice of your customers 

It is difficult to understand user needs without sufficient data or feedback. Without insights directly from users, product teams are prone to making decisions based on assumptions and guesswork. This can lead to choices that fail to solve real problems or address what users want. Teams may add features users don't need, overlook areas for improvement, or misdiagnose where the product is falling short. 

Netflix, a leading streaming service, regularly conducts user research to improve its user experience. By analyzing user feedback and behavior patterns, they have made small but impactful changes to their interface, such as personalized recommendations and intuitive navigation, resulting in improved customer satisfaction and engagement.

Customer feedback is invaluable for companies, yet it can be challenging to synthesize all the voices in a clear direction. While vocal users provide direct insights, their needs may not represent every customer. Companies must balance actively listening to individuals with zooming out to see the bigger picture revealed through usage metrics and behavioral data.

Establishing ongoing channels for a diverse set of customer perspectives allows for deeper qualitative understanding. Customer advisory boards, user testing groups, and frontline employees can provide ways to regularly connect with and learn from a sample of users. At the same time, following up with detached users can uncover pain points to address more broadly.

All of this feedback should be considered in the context of company strategy and goals. Responding to each customer request could cause you to lose sight of the broader vision. The aim is to understand customers’ needs holistically, not let any one voice or data point dictate decisions.

By analyzing insights from both qualitative and quantitative sources, companies can truly grasp customers’ perspectives. Listening is crucial, but so is synthesizing feedback thoughtfully to prioritize moving products, services, and strategies in the right direction. The full picture comes into focus by balancing engaged user opinions with zoomed-out usage data.

Once you understand the full user experience, share insights cross-functionally and align all teams to a roadmap that’s rooted in user feedback. Research should inform priorities company-wide, not just an individual product or team. Great product teams prioritize initiatives that solve urgent or pervasive user problems over nice-to-haves. Fixing pain points and frustration builds trust and loyalty. You can also use this research to inform tradeoff decisions between improving existing products or building new ones. 

Yet, just because there is a user need doesn’t mean it’s smart to solve. We must balance this with cost. To do this, align your business outcomes and key metrics to your research and discovery efforts. This puts meaningful data behind potential opportunities. The goal is to feel confident that you are spending your budget in the right areas. 

Understanding your position in the competitive landscape

Conducting market and competitive analysis poses challenges for many product teams. The product landscape is often complex, with hidden nuances in customer segments, pricing models, and positioning. Limited or poor quality market data makes it difficult to size opportunities or fully understand customer needs accurately. And in fast-paced markets, competitors' new offerings create blind spots if the analysis isn't continually updated. 

These gaps can lead to flawed evaluations of the product's status versus alternatives. For example, competitive improvements in features or user experience may be underestimated. Or emerging competitors may be entirely overlooked if the analysis relies on outdated information. 

Apple's iPhone product line consistently undergoes both small improvements and major redesigns to stay competitive. While incremental updates address immediate user needs, Apple also undertakes full redesigns to introduce groundbreaking features and stay ahead of competitors. The introduction of Face ID and the removal of the home button in iPhone X marked a significant redesign, enhancing security and user experience.

High-quality market analysis requires not just comprehensive data, but also insight into future trends and developments. Without that level of depth, product decisions risk misalignment with real market dynamics and competitive threats. Teams should make ongoing market analysis a priority, dedicating resources to gather and interpret intelligence so they can make reliable evaluations.

Managing technical debt 

Staying current with technological advancements presents a challenge for many product teams. As infrastructure and platforms rapidly evolve, products built on outdated technology can suffer from poor performance, limited scalability, and security vulnerabilities. However, assessing the pace of change and knowing when and how new technologies will impact the product is difficult. Teams risk either being blindsided by the need for urgent upgrades or investing prematurely in cutting-edge tech that isn't mature enough. 

Adobe, a leading software company, recognized the need for a major rebuild to transition from its traditional software model to a cloud-based subscription service. The redesign of their Creative Suite into Adobe Creative Cloud involved a significant technological overhaul, enabling real-time collaboration, automatic updates, and cloud storage for their customers.

Addressing technical debt can be approached in several ways - as a prioritized feature, allocated capacity, or focused effort.

Some teams treat upgrading technical debt like any other feature, evaluating the user value versus development effort and prioritizing it accordingly in the backlog. This allows it to be weighed against new capabilities.

Other groups allocate a fixed portion of capacity each sprint for tech debt, setting aside developer time specifically for upgrading and refactoring. This ensures a consistent investment regardless of other feature work.

An incremental approach creates a rotating team with dedicated sprints to focus solely on addressing a specific area of debt before rotating to the next. This intensity over time incrementally improves quality.

The best approach depends on factors like the severity of debt, user impact, and development resources. For example, allocating fixed capacity works when tech debt is manageable within typical sprint capacity. Critical vulnerabilities are better handled as prioritized features. An incremental "tech debt squad" might suit a legacy system needing intense modernization.

Regardless of approach, addressing technical debt should be accounted for, not left to chance. Proactively managing debt alongside feature work is key for sustainable quality over the long term. Failing to do so will only compound maintenance costs and risks down the road.

Evaluating factors like dependent software roadmaps, compatibility risks, performance benchmarks, and security threats requires significant research and foresight. But without that understanding, there are consequences. Obsolete codebases grind progress to a halt, while patchwork upgrades create technical debt. 

Proactive technology analysis and planning are essential to balance leveraging advancements with pragmatism. Partnerships with tech companies, proof-of-concept testing, and prototyping can help teams make informed decisions on when to phase out legacy systems versus adopt innovations. With technology moving fast, teams must stay vigilant and informed to avoid getting left behind.

Managing resource constraints

Product teams often grapple with tough trade-offs between incremental improvements and complete redesigns due to limited resources. Budget constraints may preclude large investments, while tight timelines demand minimally viable launches. Lack of specialized skills like machine learning expertise restricts explorable options. This forces teams to choose between building on existing systems or starting fresh. 

The large upfront costs of re-platforming can appear daunting, causing teams to favor temporary patches over long-term solutions. However, this accrues technical debt and ongoing maintenance costs. On the other hand, committing to costly rebuilds too often diverts resources from revenue-driving features. There is rarely a perfect answer. 

For example, Facebook's News Feed algorithm is continuously refined through small improvements based on user feedback. However, they also invest significant resources in major redesigns, such as the shift towards prioritizing content from friends and family, to align with their long-term vision and strategic goals.

Effectively managing resources and assigning teams starts with comprehending the company's current business goals and market landscape. This requires understanding who the target customers are now versus in the past, along with their evolving needs. It also means knowing what forthcoming market shifts or new opportunities take priority. With this knowledge, teams can be allocated to the projects and products that are the biggest drivers of growth or cost savings for those new market conditions.

Additionally, an attitude of evaluating existing products objectively is important - the "keep, toll, leave, obsolete" (KTLO) mentality. Teams should assess each legacy product or platform on its own merits, not based on sunk cost fallacies or emotional attachment.

With insights into market trends, customer needs, and objective evaluations of existing products, data-driven trade-off decisions can be made. Resources can be realigned away from truly low-value legacy items and toward high-impact new products or features. A solid understanding of the current business context allows teams to be reallocated and priorities shifted to where the company needs to be for the future.

Making these resource and portfolio decisions holistically, with the bigger picture in mind, enables more agility and value than continuing the status quo path.

As product and digital executives navigate the decision-making process of making small improvements or undertaking a full redesign or rebuild, they must address challenges related to user feedback, market analysis, technological advancements, scalability, resource limitations, time constraints, risk tolerance, and strategic alignment. 

By employing strategies such as user research, competitive analysis, phased improvements, stakeholder alignment, and external expertise, decision-makers can mitigate these challenges. Real-world examples from companies like Netflix, Apple, Adobe, and Facebook demonstrate the successful implementation of these strategies, leading to improved user experiences and long-term success in the dynamic digital landscape.