Product, Projekt & Agile: Thoughts and articles that touch and cover Product and Project Management, for the majority with Agile Methodologies. These items include Market Observation, Competitive Analysis, Backlog Prioritisation, but also choice of tools and technology.
Product Management Predictions: With January already over, it’s a bit late for annual forecasts. But then again, looking into the future is a secret superpower every Product Manager should look to develop. Therefore, it’s never too late to have an understanding of what comes up next. Mason Adair of Digital Product People did so for the profession itself.
Ten Wild Predictions, One True Story and some Solid Career Advice
From the article
Just like the industry is changing. And the article makes an effort to put into relation the different aspects Product Management has. Mason starts his thoughts by looking into public available metrics that indicate the importance and projected relevance related to management of products. In this analysis, related topics range from Agile, Minimum Viable Product, Design Thinking, Lean Startup, Product Market Fit, Rice Prioritisation and Net Promoter Score all the way to Jira, Trello and Asana. With an analysis of how relevance for these topics changed over time, the article goes into setting the scenes for professional trends that influenced the past years. These include economic environment, the introduction of new technology, a demographic shift, increasing societal fragmentation and climatic change.
Product Management Predictions shape the conclusion in his article: 10 wild predictions I believe are not that wild. The top most prediction, Product arriving at the C-Level, is almost no prediction anymore. Digital companies already have recognised the importance to actively influence direction towards customers.
Product First Step Feedback: Having worked in customer facing roles most of my career, I have experienced first hand how important it is for clients to get quick impressions of a product. Opportunities to leave that impression are often limited.
The other night, a colleague argued most products don’t even need a UI. And a UI won’t even be necessary for products that aim at developers as their audience. It may be unnecessary for specific, complex products. And in general, I won’t disagree. Such products exist and still require a good first impression. Browsing open source directories at Github, popular projects come with good documentation. A readme.md that comes with building and running instruction.
In the IaaS/PaaS/SaaS world, popular tools come with first step tutorials. Quick tours to get potential users started in minutes. Google apparently made this a release requirement, since virtually all products ship with a “Get Started in 5 Minutes” section to start with.
When I came into the product management role, I was a strong proponent of UI driven products. In hindsight, this believe was driven by the pure marketing thought of it. A UI shows better at trade fair booths than a terminal.
With more technical products, the readme is the last resort. And with that, an opportunity to gather feedback is gone. The UI can implement tracking and analysis to build a feedback channel for Product Managers to understand how the new feature actually is perceived.
In the software, provided it is delivered in source, the first step that could possible send telemetry, is the build process. And to drive adoption, you have to offer the customer a good first impression in documentation, before he can build your component. Should the documentation not deliver on this first step, you lost a customer even before he saw the product. If you are in the situation to receive feedback on this first impression, take that very serious.
Product Owner vs. Product Manager: Product Management is a challenging role and requires diverse skills. Large organisation often introduce a split between two similar, close roles – Product Ownership and Product Management. Both requires a large set of skills.
Jordan Bergtraum, The Product Mentor, a mentor at The Product Guy, leads a conversation on this split.
As a concept, the North Star principle gained a lot of attention in Product Management recently. Amplitude, a vendor of analytics tools, has a guideline to this concept. Their playbook walks product managers, those that want to enter the domain or even those just curious about methods and principles through the ideas. But also sets the scenes for potential applications by walking through exemplary goals to achieve with this approach.
The playbook comes in 7 chapters, starting by describing the ideas to apply with the North Star concept. Only after the introduction the playbook enters the practical application of the concept, and with a chapter on product metric checklist checklists, it emphasises the importance of metrics. With this it also stresses the importance of selecting the right metric and not to lose a product in vain. E.g. active users would be the wrong metric, given the goal that shall be achieved.
More practical guidelines come with the chapter on running workshops in part 3, and the chapter on defining the right guiding metrics. In between, the document also gives success stories: there are sections that talk through a successful implementation of North Star at Netflix. But also Amplitude is leveraging the methodology and shares their experience in a section.
The closing chapters dedicate to debugging the processes attached, implementing them and over time changing directions.
In all the recent hype around the method, the key take away is to simplify ideas for your organisation. The approach is supposed to make it easy for your teams to understand the direction the product is taking. And even more following this direction. For a product management, communicating ideas should be a core skill. This approach gives great tools in doing so.
The guide to discovering your product’s North Star to improve the way you manage and build products.
Wie mehrereQuellenheuteberichtet haben, ist der erst neuerlich verfügbare Mac Pro in der höchsten Ausbaustufe teurer als ein Tesla Model 3 in der “Performance” Ausbaustufe. Apple ist nicht dafür bekannt, billige Hardware zu produzieren, aber 62.568,00 € sind selbst für die bekannten Verhältnisse beeindruckend.
Man bekommt dann für den Preis immerhin:
2,5 GHz 28‑Core Intel Xeon W Prozessor, Turbo Boost bis zu 4,4 GHz
1,5 TB (12 x 128 GB) DDR4 ECC Arbeitsspeicher
Zwei Radeon Pro Vega II Duo mit jeweils 2 x 32 GB HBM2 Grafikspeicher
4 TB SSD Speicher
Apple Afterburner Karte
Edelstahlrahmen mit Rollen
Magic Mouse 2 + Magic Trackpad 2
Magic Keyboard mit Ziffernblock – Deutsch
allerdings keinen Monitor. Aber dafür wird eine 8TB SSD später noch verfügbar gemacht werden.
Python, the programming language, gained lot’s of popularity only in the past decade. In particular for big data applications, machine learning and data science the language is almost without alternative. But also for tool development or web applications backends, Python has huge adoption. Reasons are it’s huge ecosystem and a friendly, constructive community. Despite it’s newer competitors it has been around for 30 years. One of the most appreciated benefits is the steep learning curve, that allows virtually everyone to understand Python code.
Dropbox has an interview with Guido van Rossum, who published the first version of the language in 1989. The conversation revolves around the purpose of code and how python helps improve cooperation and productivity.
“You primarily write your code to communicate with other coders, and, to a lesser extent, to impose your will on the computer.”
Part of the compelling nature of SaaS Products is the possibility to understand the user and improve on the go. Any Product Manager will literally have to understand what are the use-cases for customers and how to focus on the important areas. Just recently our team led the debate which metrics would be the right ones to focus on.
Nancy Wang, Head of Product Management at Amazon Web Services, highlights six product metrics enterprise SaaS companies should track.
In this Article, Nancy Wang, head of Product Management at the most successful cloud service providers, shares her insights on important metrics to keep an eye on. The possibility to understand often goes overboard and requires focus.
The case under discussion in the article revolves around paid products. Derived metrics are a foundation that serves as a blueprint to other products in the SaaS space. Goals differ, but ultimately, to make a product successful, it requires an understanding of how successful customers were, using the product. Following the established funnel pattern, users are being segmented into funnel. Along that funnel, the metrics acquired need to reflect the stage of the journey the user is on.
At the top of the funnel, most often the interaction is anonymous and requires profiling to understand the audience coming in. Further down in the funnel, metrics capture engagement and transaction. Towards the end of the funnel, the metric needs to relate to retention.
All too often, two departments are burried in deep arguments for most of their days. While business, the outbound oriented Product Management department, leads customer conversations and verifies business requirements, engineering is pushing towards a better product.
Their goals are not always aligned despite the necessity to build a product together. Overcoming controversial goals can be difficult, yet frustrating to Product Managers in their quest to build better products.
Itamar Gilad shares a few thoughts how to overcome this gap.
Managers and product managers are often frustrated by the apparent lack of care the development team is showing for the needs of the…