To me, thinking and bleeding “real time” is the core of the term “digitalization” (which I am so sick of hearing, but that is another topic). And it is mind-boggling how many businesses do not consider themselves “real-time”. Interestingly this applies to both established as well as new business and basically across all industries. Simply because you are selling something physical or not time critical does not mean you can ignore it.
Your (potential or actual) customer has her demand / interest/ engagement right now. NOW. Not in 5 minutes, not tomorrow. And you better be prepared for that moment having processed all the available and relevant information of the past and be able to fulfill the need as fast as possible. Some applies to internal stuff, why limit yourself to some snapshot of the past? The past just concluded and simplifying your approach by just processing the data of the last month or yesterday simply is not enough, you will never be able to react to the latest events (a value from a sensor, the click of a consumer, the change in your inventory system, …) which in many cases will make all the difference. …
AI (as in Artificial Intelligence) and ML (as in Machine Learning) are the latest buzz in the early stage startup and tech scene and as such there is a lot of startup stories and pitch decks build around these magical technologies.
Most of these pitches follow a common pattern / storyline:
An amazing aspect of working in the venture capital space is the continuous debate how this business makes the most sense as in can be most lucrative for a venture firm and its investors (Limited Partners) over a longer period of time (the longer period of time is important here to somewhat lessen the effect a single massive hit can have on performance). I constantly find myself in really interesting discussions about this topic and this is probably one of the most blogged about topics by VCs.
The discussions interestingly cover almost all aspects of the setup of venture firms, from sizes of funds (varying from 50m to >1bn), the investment approach (focussed large investments vs. lots of smaller ones) to the team setup (larger operating team supporting companies vs. small investment team with basically no support staff) and so on. Even which KPIs are most or actually relevant when evaluating VC funds which have not yet been fully returned is a continuous discussion. …