There has been a lot of discussion about the development of technologies and their Hype Cycles (Gartner) or the challenges of Crossing the Chasm (Geoffrey Moore), and especially when to implement an in-memory technology as SAP HANA:

Big Data – Crossing the Chasm in 2013! By Stefan Groschupf, December 19, 2012

However there is a clear mathematical recommendation when to invest into a new technology based on two assumptions:

- The overall value of a technology for any organization is limited and decreases linearly from its introductions:
- Innovators get the full value from the ability to offer completely knew and so far technically impossible business models.
- Early adopters get the value of differentiation where they can offer products and services in a variation and combination that competitors without that technology cannot.
- Joining the majority early avoids the opportunity costs of falling behind and losing market share by competitors using a widely accepted technology.
- Joining the majority late avoids the opportunity cost of being pushed out of a market by competitors using a best practice technology.
- Eventually the technology is not supported any longer and has to be retired.

- The cost of implementing a technology decreases proportionally:
- At the point of innovation the technology is hard to implement due to the lack proven implementation procedures, incomplete or fragmented documentation and product defects.
- Early adopters benefit already from first implementation experiences, better documentation and fewer product defects.
- The early majority benefits from proven implementation procedures, complete documentation and rare product defects in combination with implementation partners understanding the technology.
- Late adopters can leverage the mass adoption of the technology by outsourcing both its implementation, operation and maintenance.

The following model, where the y-axis represents value / costs and thy x-axis time, is based on those two assumptions only:

- The orange triangle and orange graph (which are equivalent) represent the remaining realizable value from the time of implementing a new technology until its retirement.
- The red graph represents the cost of implementation at any given point in time.
- The blue line segment between the orange graph and the red graph, and the blue graph (which are equivalent) represent the realizable benefit, as the difference between the remaining realizable value and the cost of implementation at the point of implementing a new technology.
- This benefit has a maximum, where the pink graph intersects the x-axis.
- The green part of the x-axis where the red graph is below the yellow graph represents the window of opportunity, when any value could be realized at all, i.e. the realizable value being larger than the costs. Prior to this window of opportunity the implantation costs for a new technology are usually too high but might potentially be lowered by bringing the technology inventor into the implementation project. After this window of opportunity the benefit until the retirement of the technology would not outweigh its implementation costs except if it was a precondition for another new technology for example.

## Summary

Based on the two assumptions, that the realizable value for any technology decreases linearly from its time of availability until its retirement, and the that the cost to implement any technology proportionally decreases from its time of availability, there is one most valuable point in time to adopt this technology as well as a window of opportunity where any value in adopting this technology could be realized at all.

In terms of HANA, SAP see the chasm already crossed and the phase of early adoption completed with enough ramp-up customers live with SAP HANA to prove the point. Therefore there is the opportunity now to implement SAP HANA with the early majority and gain competitive advantage over competitors that still hesitate, e.g. with BW on HANA by analyzing profitability in real time and correcting pricing mistakes instantaneously or with Operation Process Intelligence by detecting nearly missed KPIs and correcting the issues before they become problems.