#6: Engineering Considerations That Product Managers Should Watch out For

Aviral Vaid

Hatched by Aviral Vaid

Oct 06, 2023

4 min read


#6: Engineering Considerations That Product Managers Should Watch out For

Alignment through OKRs and Hypotheses: A Powerful Approach for Product Managers

In the world of product management, two key aspects often come into play: engineering considerations and the need for alignment. Both of these factors are crucial for the success of a product. In this article, we will explore the intersection of engineering considerations and alignment through the lens of real-time requirements and the use of Objectives and Key Results (OKRs) and Hypotheses.

Real-time requirements play a significant role in the development of a product. Product managers need to carefully analyze whether the results of their algorithms can be calculated in advance or if they need to be calculated in real time. This consideration affects not only the design of the product but also the choice of storage methods and data collection methods. When data is added or modified, it is essential to identify which models need to be re-run or re-trained. Additionally, the speed at which these updates should happen must be determined, taking into account acceptable Service Level Agreements (SLAs). The rate at which data is collected and accumulated further impacts the design of pipelines and storage methods. These engineering considerations need to be monitored closely by product managers to ensure the efficient functioning of the product.

On the other hand, alignment becomes paramount as products and teams scale. However, the common trap of trying to control everything to prevent misalignment often stifles creativity, demotivates teams, and slows down the overall velocity. This is where the use of OKRs and Hypotheses comes into play.

OKRs provide a framework for setting goals and defining the key results that are expected from those goals. The general rule of thumb is to have no more than five key results per objective. The "why" behind launching a product or the expected benefits are the outcomes that product managers aim to achieve. Key results should be measurable, following the SMART goals principle. OKRs can be used at various levels, serving as both long-running, lagging indicators and tactical, leading indicators. The power of OKRs lies in their solution-agnostic nature, allowing teams the freedom to determine how they will achieve the objectives.

Hypotheses, on the other hand, complement OKRs by providing a framework for experimentation. Hypotheses consist of two statements: the experiment or "bet" that the product manager wishes to try and the expected outcome. Additionally, the impact of the experiment and how it will be measured are also defined. Hypotheses serve as the means to achieve the objectives set by OKRs. They provide a way to measure progress towards the vision and ensure teams are swimming in the right direction. It is important to note that discovery should inform these hypotheses, and the roadmap should consist of both planned bets and "fuzzy" opportunities aligned with OKRs.

To maintain alignment, product managers should provide direction and boundaries rather than cascading solutions or micro-managing. OKRs and hypotheses should correlate, serving as common goal posts to keep teams loosely aligned. Empowering and trusting teams to make their own decisions is crucial, as seeking approval or blessings from higher-ups can create dependencies and bottlenecks. Less is more when it comes to metrics, and product managers should avoid picking too many. A rule of thumb is to have no more than three metrics or key results for both OKRs and hypotheses. It is also important to differentiate between leading and lagging indicators, with OKRs being more lagging indicators and hypotheses serving as leading indicators with shorter feedback loops.

In conclusion, engineering considerations and alignment are two critical aspects that product managers should watch out for. Real-time requirements, data dependencies, and data collection methods all contribute to the successful development of a product. Additionally, the use of OKRs and hypotheses provides a powerful approach for achieving alignment across multiple teams and products. By setting clear objectives and measurable outcomes, empowering teams, and maintaining a balance between direction and autonomy, product managers can navigate the complexities of product development and drive success.

Actionable Advice:

  • 1. Regularly assess the real-time requirements of your product and ensure that the necessary engineering considerations are in place.
  • 2. Implement the use of OKRs and hypotheses to drive alignment across teams and products. Set clear objectives, measurable outcomes, and empower teams to make their own decisions.
  • 3. Focus on a limited number of metrics for both OKRs and hypotheses, and differentiate between leading and lagging indicators to ensure a balanced approach to measuring progress.

By following these actionable advice, product managers can effectively navigate the intersection of engineering considerations and alignment, leading to the successful development and growth of their products.

Hatch New Ideas with Glasp AI 🐣

Glasp AI allows you to hatch new ideas based on your curated content. Let's curate and create with Glasp AI :)