AI/ML in B2B Enterprise Life Cycle Optimization

I have worked more than 25 years in B2B High-Tech organizations in sales / presales and professional services leadership roles and while used technologies and processes have changed, a key aspect of the business — the complexity to create sound project proposals has not:

1. Writing offers/proposals/engagement letters/statement of works remain a “custom”, manual, labour intensive process
2. Even worse, on average 80% of the bids get lost so that all the effort invested (Sales, Presales, PS Pricing/Quoting) is lost
3. Ambitious initiatives by PS Operations to “standardize” and “package” services to make the processes easier, repeatable and scalable using CPQ tools have failed to deliver on the promise, the tools struggle with capturing the complexity of the business, they are or built so complex that field users simply bypass them or when used they only work for simple configurations well but as soon as a certain complexity is reached Architects are forced back to the drawing board
4. Part of the companies keep the burden of quotations on the field architects, they are the best in position to achieve proper scoping, but in many cases they are the most scarce resources, so while the skillset enables them to do the best job, the characteristics of the business (80% of the work lost) makes the productivity performance a nightmare
5. The other part of the companies have pushed the burden onto specialized back-office pricing specialist, while best positioned to work on the provided tools, their gap in technology expertise and field experience lead to scoping issues, lead to execution issues so that two pricing specialists using the same tools come up with complete different price points, making a proper alignment between Sales&Presales and PS organizations even more difficult
6. The “learning” of the organization happens once or twice per year in the PS operations back office, bright people try to apply common sense, business knowledge and statistics to come back with improved tools with even more SKU packages or even more complex configuration rules, but the noted issues in the field remain

… and many use the constant argument that “custom” projects are simply what they are, every engagement is “unique” and has to be therefore complex….

…but while every snowflake is unique in its ultimate structure, a clever algorithm can easily create millions of unique snowflakes without any human needed to describe individual complexity….

… this is why I have embarked with FluidX on a mission to disrupt this process with AI/ML enabled intelligence…

Gue