Predict business startups success example How to do it

Predict business startups success example How to do it

Apr 27th, 2016

Predict business startups success example How to do it

ORE applied to Startups development came up when we read examples of “archival analyses” on startups. Researchers used data mining to show that:

  • board “age”,
  • “gender”,
  • “capital”,
  • “IP” and finally
  • “race”

have insignificant effects (after 5 years) on either merger/acquisition rate OR survival of operations of startups. Those results left the authors of the research (Kaufmann Foundation) with the feeling that “something was missing” in this type of analyses. Those results stimulated Riskope to look for solutions.

We decided to follow the general ORE’s procedure. Thus we started by the deployment by defining a functional model on which to build the risk analysis of the start-up.

Finally, we identified potential hazards to the company’s functional model (process of the company) functions. The hazard identification spanned from R&D to IP protection & development to valuation. It was a  systematic approach, leading to a unified risk integration. One that is easily scalable and repeatable.

Exposing the assumptions of the business plan

We exposed, based on a priori data, the underlying assumptions of the startup’s business plan. To do that we looked at the resources. That is how those resources are used, transformed exchanged. The resources are:

  • human (management),
  • cyber,
  • energy electricity,
  • feeds,
  • etc..

We then provided estimates of probabilities of failure with their uncertainties. An important informations are their key driver(s) for each hazard and each function as parameters of the ORE applied to Startups application.

Predict business startups success example How to do it

Fig. 1 Scheme of the ORE (Optimum Risk Estimates) continuous process. Scalable and drillable from cradle to grave for any project, alternative, operation.

We defined probabilities by consensus among analysts (MBA students). However probabilities can result from a blended approach (experts-analysts-IoT-models-statistics…).

We finally built a Hazard and Risk Register using ORE systematic procedures.

We did not perform a market overview, market research, corporate legal review, or technological feasibility of the product or service. As a matter of fact we assume DD, Business Plan, etc. deal with these in detail.

However, we focused on the potential hazards on each function.

The classic Due Diligence (DD) approach and its potential mishaps

We discussed the classic DD approach in a prior blogpost 

We can summarize ORE value proposition as:

  • a quantified FMEA
    • with the systemic approach of a HAZOP,
    • without the necessity to delve into the smallest components, at first, as ORE analysis/hazard identification is SCALABLE ( from the tile modelling tool).

Within ORE, FTA, ETA, numerical probabilistic models as well as big data algorithmic analyses can be used. The purpose is to evaluate rates and probabilities of events.

One can push Consequence analysis to levels of detail pertinent with the considered system.

ORE shifts the focus on the process or function(s) of the considered system in terms of success criteria.

ORE’s approach allow to study, from the beginning, how to increase system’s resiliency , what can be changed to shift toward an anti-fragile state, from cradle to grave of a project (a start-up).

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Category: Consequences, Optimum Risk Estimates, Risk analysis, Risk management

One response to “Predict business startups success example How to do it”

  1. William Ferme says:

    Dear Sir,
    I am small business mentor specialising in Start-Ups in Melbourne, Australia. I am friendly with an Australian company called IMENCA that has produced software called BEC ( Business Evaluation Calculus ) that helps entrepreneurs determine their chances of success. Results indicate that it is accurate to about 80%. I would recommend your organisation to examine it.
    Bill Ferme MBA. M.Sc. C.Eng.

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