Product Management for Corporate Glue AND Lubricating Oil

Product Managers have a fascinating, all-encompassing role. They can be called many things, CEO of the product, Janitor, Super User. See Product Manager is a janitor basically.

All other business functions are well understood: 

• Engineering develops the product
• QA assures that the product 
• Sales converts a product into justifiable business value for each customer
• Marketing communicates the product proposition to a market of similar users / buyers

etc

But what do Product Managers do? 

• Product managers are frequently the glue that keeps the rest of the business functions inside a technology organisation stuck together. They fill in the cracks in between all these business functions.
• And they are the corporate 'oil' that lubricates other business functions within the company, making each function more efficient and in better harmony with each other.

Example

The next version of the product is coming. It's in Engineering. Product Management has defined the requirements of the product and during the build cycle, it assists with dilemmas and issue resolution.

QA is shaping up to receive the product, but this new version is more sophisticated than the previous version. The QA team need to understand the common use cases / user flows in order to write system / regression tests. They rely on Product Management for guidance.

Marketing is familiar with existing positioning, but this latest release opens up new markets and positioning. They rely on Product Management for guidance: what are the USPs? what are the best use cases? how should it be positioned and to whom? 

Sales may not be able to help for lots of reasons - they want to sell the existing products, not ones that aren't on the price list yet. The rest of the company is dependent on the Sales team selling the existing product in suitable volumes in order to pay the salary bill each month - you really want them sticking to the knitting and selling what's in the warehouse now, not yet-to-be-proven products still on the production line.

Additionally, they have had limited exposure to it: feature and functions aren't well understood yet, positioning isn't developed, use cases and case studies are embryonic at best

Account Management and Support want to know what's different about the new product and how can it be positioned to existing customers and how can they benefit most from it. Is it as good as the existing product? Can existing customers try it before they buy it etc? What the known limitations?

So, often it is the product manager / marketer that goes prospecting for beta customers and manages the beta programme(s) to their successful (hopefully!) conclusions. See the The challenge of beta programmes and Product Launch vs Release vs General Availability vs Deployment.

As a result, it is Product Management who is at the heart of technology product company, acting as its glue and the oil - and that's not contradictory!

See also How everyone else views the first-in-post product manager

ChatGPT for product management

With the release of OpenAI’s ChatGPT at the very end of November last year, there has been an explosion of enthusiasm. Here’s their trajectory to a million users!

(Thanks to Azeem Azhar of Exponential View)

Initially, the response was ‘Look at this cool poem that ChatGPT wrote.’ Thankfully more considered use cases are now developing.

So here are my thoughts on how ChatGPT can help Product Managers:

Broad Use Cases	Use Cases for Product Management
Summarisation of a long body of text	Summarising large amount of texts for requirements analysis chatGPT is surprisingly competent at summarising text eg for condensing a whole list of free-form product requests from customers into a couple of pithy themes.
And the inverse, extrapolation of short body of text.	Writing product descriptions for product marketing. a. Reinterpreting features to benefits b. Rewriting product marketing copy for particular audiences
Variation of an existing body of text	Wearing your product marketing hat, you have written some descriptive words, but they need some help or the body of text needs to be shorter to fit into a text box on the website or on your PowerPoint.
Initial research into a topic or industry	As Product Managers, we spend a lot of time trying to make sense of a market / customer / technology / product / service. I can see myself using chatGPT as a great start to understanding the four walls of a market. Market research: what do I need to know about XYZ? What’s new and important in the XYZ sector? Who has the competitive advantage and why in XYZ sector? It’s great a high-level summaries, but not good enough for the details that matter.

As always the devil is in the details, but at least it gives the Product Management some boundaries and some structure to start with. And you would never submit the output from ChatGPT as your completed, best thoughts, BUT it does provide a start and save on that first half hour / blank canvas problem / writer's block when you’re wondering where to start from.

ChatGPT for managers

One great advantage is that it can create consistency when you have review or compare work from multiple teams. By getting your teams to start with ChatGPT's output, then at least all the teams have started from the same point with their use case (not using a template).

What it won't do effectively?

Some have claimed that it could be used to write product requirements. Nope – well, not to a meaningful level and certainly not good enough to give to a developer.

Cute Use Cases

• There’s one elegant use case of writing a Value Model Canvas.
• I Interviewed ChatGPT for a PM role, and it almost got the job

Side Notes on OpenAI

• Who are their investors - it's always useful to know where the money flows. 
• Y Combinator
• Peter Thiel (founder of Paypal)
• Reid Hoffman Foundation (founder of LinkedIn)
• Khosla Ventures 
• Elon Musk did invest, but has now sold off his stake
• Microsoft Ventures ($1bn investment in 2019 + MS has built a supercomputer in Azure to support OpenAI ML research)

OpenAI have more complex corporate structure than most: there is for-profit corporation OpenAI LP and its parent company, the non-profit OpenAI Inc. AND in 2019, OpenAI transitioned from non-profit to "capped" for-profit, with profit cap set to 100X on any investment. (Source: Wikipedia)