Lists of business trends tend to fall into two types – those that look into the future and those that survey the past. Predictions about future trends are tricky because of the uncertainty of them coming to pass. Lists of trends that survey the past should be easier by definition, right? After all, what’s happened has happened. Let’s look at some of the biggest trends we identified in 2022.
Trends (still) impacting the newly converted
Organizations that have more recently recognized the importance of product management to the success of their business are those that are transitioning from being “sales-led” or “customer-led” to “product-led.”
Agile vs. agile
“Are you Agile, or are you agile?” Adopting Agile methodologies like Scrum, Kanban, eXtreme Programming, or some combination of the above has been a trend, or some might say a craze, affecting digital product management for many years. The process has been going on long enough to spawn backlashes proclaiming its demise. As others have said, the idea that Agile methodologies are a thing of the past is a gross exaggeration. Still, the problem that this discussion raises is a real one with which many organizations continue to struggle.
At issue is the difference between Agile (capital “A”) methodologies and an agile (small “a”) mindset. Yet many organizations continue to jump head-first into the adoption of Agile practices. And they do this without an understanding of why these practices work. Organizations that fail at Agile practice adoption often haven’t taken the time to embrace the agile mindset.
Unfortunately, this trend is likely to be with us for a while. Fortunately, many companies do eventually get through botched implementations and false starts. Failure is a great teacher.
Another persistent trend is the continued growth of an appreciation for grounding decisions in data – both quantitative and qualitative. This trend has supported the emergence of the Data Product Manager as a role on the product team dedicated to the process of collecting, organizing, storing, and sharing data within an organization. At the time of writing this post, there were 525 postings on LinkedIn for positions in the U.S. with this focus. When broadening the scope to include data scientists and data analysts, who often work closely with product managers to answer questions with data, the open positions swell to almost 7,000.
Outcome-driven vs. feature-based roadmaps
If you are unfamiliar with the difference between these two types of roadmaps and why it matters, let’s quickly unpack that. They showed a list of features on a release timeline: this quarter, we will ship features a, b, and c. The next quarter will feature d, e, and f. There are several problems with this type of roadmap:
- Feature-based roadmaps are often inaccurate because forecasting the completion date for a new feature is imprecise.
- They don’t typically reflect the reasons why any feature ships.
- Little attention is paid to whether the shipment of a specific feature led to a profitable outcome. The act of shipping a feature is celebrated rather than the achievement of a measurable result.
On the other hand, outcome-driven roadmaps are very different. They focus on the results that the team is looking for. Either way, they recognize that the product changes are more hypotheses than guarantees. Moreover, they embrace the uncertainty of the timeline. Finally, they accept the agile (small “a”) reality that priorities change.
In full disclosure, placing this trend on the list of those affecting organizations early in their product management journey reflects a bit of a bias to which some may object. The bias is based on the judgment that those still using feature-based roadmaps fall low on the product management maturity scale. Although some companies have been on their product management journey for many years and still use feature-based roadmaps, their reluctance to accept the limitations of this approach and embrace an outcome-driven approach is holding them back.
Trends for product management leaders
While the list of trends above is relevant to those who are further along their product management journey, they are no longer top of mind. Whichever side of the ongoing debates these organizations fall on, the companies in this group have picked a position and are now looking at a different set of concerns.
- Optimizing data pipelines
- Product Ops: hero or villain?
- The extent and limits of product management authority
A warehouse-first approach to data
The next step after recognizing and embracing the importance of using data throughout the organization is to figure out how to deal with the pitfalls many companies fall into when they first embrace data-driven decision-making. As many product managers learn, it’s not enough to have the data; you have to be able to put it to use. The inability to perform analyses that require combining account data with usage data is a frustrating roadblock. Learning about an incompatibility between systems initially chosen as point solutions is a common facepalm moment as product leaders mature in their organizational data requirements.
One solution to this problem that is growing in popularity is to take a “warehouse-first” approach to data collection. In other words, the data warehouse is the source of truth and the central node in the data pipeline strategy. Account, app usage, clickstream, and marketing data are all stored in a data warehouse where it is cleansed and transformed as necessary before being pushed out to other tools like marketing automation.
The advantages of a warehouse-first approach to data are compelling, especially considering the ability to avoid vendor lock-in resulting from key data being imprisoned in a proprietary database. The challenges, however, are also significant. Key pieces of the puzzle are lacking, so you may need to adopt a hybrid approach until the tool you need supports the ability to ingest data from an external source. In other cases, the tools exist, but issues can arise for those handling healthcare or other sensitive data that cannot leave the U.S. due to regulatory restrictions. If you find yourself looking into the tools available, be sure to verify whether the vendor can guarantee HIPAA or other relevant compliance before going too deep on an evaluation.
Product Ops: hero or villain?
In February 2022, product management author, blogger, consultant, and pundit Marty Cagan lit up product management discussion groups and Slack channels with his post, “Product Ops Overview.” In this controversial post, Cagan identified six distinct definitions of the Product Ops role that he describes as “most damaging, to most valuable.”
- Reincarnated PMO Model
- Two-in-a-Box PM Model
- Delegated Product Leader Model
- Product Operations Rebranded Model
- Product Marketing Manager Rebranded Model
- Force Multiplier Model
The post generated controversy because his opinions hit close to home for many people. The Product Ops role has been proliferating on product-related job boards for several years, and it has solved a lot of problems for a lot of organizations. Cagan would likely argue that those problems arose from more fundamental problems in product management practices. Regardless, the debate over the role of Product Ops within a product management organization is not over.
The extent and limits of product management authority
A popular product management book on product leaders bookshelves is Influence Without Authority by Allan R. Cohen and David L. Bradford. This book describes how to use an understanding of what motivates others to achieve mutually beneficial agreements when the ability to control the actions of others through managerial edict doesn’t exist.
The idea that a good product manager is the CEO of the product was first articulated more than 20 years ago by Ben Horowitz in his memo, “Good Product Manager/Bad Product Manager.” Horowitz has since added a disclaimer to the top of the document, possibly because of the backlash over some people taking his original concept, that a “good product manager takes full responsibility and measures themselves in terms of the success of the product,” to an unintended extreme. Some product managers have used this statement to assume authority where none exists.
Empowered product teams, another of Cagan’s contributions, are essentially the antithesis of feature teams. The latter is given a list of features and enhancements to implement that are defined and prioritized by stakeholders outside the product team. The former is given problems to solve and trusted to discover, design, build, and implement solutions that solve those problems.
None of these concepts are new to 2022, but the discussion is alive and well. At the heart of the debate are challenging decisions about how an organization will be run. As product management teams mature from infancy through growing pains associated with company expansion and possibly bumpy roads, these decisions are inevitably revisited.
Trends on everyone’s mind
Regardless of where you are on the product management maturity scale, there’s a good chance you spent some part of 2022 considering one of these topics:
- The impact of artificial intelligence
- Objectives & key results
- The great talent shortage
The impact of artificial intelligence
On the mind of virtually every digital product manager with enough capacity to think ahead a few steps is the question of how artificial intelligence plays into their product strategy. For some, of course, this question is not one for “someday” but for “right now.” The financial product manager who is not at least thinking about how they can leverage AI today is probably already falling behind in the market.
AI impacts all stages of the product lifecycle, from design to development and testing to marketing to customer service and support. If you’re not considering how AI will affect how to design, build, market, or operate your product, you can bet your competitors or future disrupters are.
Objectives & key results (OKRs)
Is there anyone who hasn’t at least dabbled with OKRs yet? This organizational management methodology has been around for decades but has exploded in recent years into one of those “everyone’s doing it” trends. Seemingly every unicorn in Silicon Valley and beyond, not to mention the largest and most successful companies in the world (Google, Microsoft, Netflix, Adobe, Intel, Amazon, Dell, GE), have embraced OKRs to align their people around the corporate strategy. A well-executed OKR implementation promises not just to get everyone in the company paddling in the same direction but also to increase morale and retention by helping every member of the team to understand how their day-to-day work supports the big, strategic goals.
The great talent shortage
Finally, a growing appreciation for the importance of solid product management has combined with an expansion in the overall jobs market to add product manager to the list of roles that are difficult to fill, along with product designer, software developer, and many others. The candidate shortage has contributed to a rise in wages which has made the ease of changing positions in search of higher pay more common, so positions are difficult not just to fill but to keep filled.