(Updated from the original on 24 June 2014, 3 December 2015)
This week, we’ve been looking at two different lifecycles: the product lifecycle and the development lifecycle – cycles within cycles!
At the macro scale we’re looking at the product lifecycle which spans its evolution from drawing board to market through to eventual withdrawal. On a smaller scale within that cycle, a product will go through many development lifecycle iterations.
If you’ve got 15 minutes handy, here’s an engaging and useful overview of Agile Product Ownership by Henrik Kniberg over on Crisp’s Blog. I also love the sketching tool he’s narrating over! (it’s ArtRage if you were wondering)
Do you spend more time writing documents about your product than actually managing it?
Many companies with a product management function become all caught up in the process, drowning themselves in increasing numbers of documents. These rapidly become overwhelming to manage, contain duplicated detail and ultimately obscure the real goal of product management, namely to create successful products.
I’m writing about one hundred things I’ve learned about being a product manager.
So much of being a product manager depends on successfully persuading and influencing others. Whether you’re presenting your product strategy, presenting a business case to the Board or talking with your customers, you need to demonstrate a good knowledge of your products and market to ensure that you come over as authoritative and credible. Continue reading →
Do you find it difficult to set appropriate financial targets for your product? Recently I’ve been attempting to simplify the process as part of my planning for my company’s next fiscal year and wanted to share an approach I’ve found helpful with you. I’ve created a straightforward spreadsheet, which you are welcome to download and adapt for your own purposes. Continue reading →
I once worked with a chap who managed an online service, which charged by amount of data stored. The service was popular and growing its revenues, however the P&L model assumed that data was stored compressed, when in fact the reverse was true. Thus, the more popular the service became, the more it lost money on running costs…