challenges we face

We have been working on this project for several months. We have made good progress but challenges remain.

  • Customer validation – persuading potential customers of the usefulness of this system to their organizations
    This task is receiving most of our attention right now. We need to describe or prove our concept in a way that elicits positive comments from prospective customers (even an interest in buying a completed product), comments  that can be shown to prospective investors.
  • Developing a working prototype of the system sufficient to prove the concept, and begin earning revenue
    We expect to do this by designing algorithms to automate a subset of data related to a key component of the strategic planning process. The result will be a free-standing product, a working prototype, a minimally viable product that demonstrates how the full product will function.
  • Gaining access to all data relevant to the planning process
    The most effective strategic planning system relies on large volumes of data, which must be identified and acquired. The relevant data will be unique to each organization.
  • Paying for data that is proprietary
    A lot of those data will be external, proprietary and costly.
  • Transforming the corporation’s internal data to make it useful for planning purposes
    Internal data about a business’s operations are important to the strategic planning process. It may be necessary to find what data exist in the corners of the organization, clean and classify them, then standard format before they can be used.
  • Persuading corporate executives to surrender some of their strategic decision-making authority
    Some executives will see the value of high-speed, high-tech strategic planning immediately. Others will see their authority threatened. Eventually, they will come accept it when they see the value it provides and its use by  their competitors.
  • Recruit the computer science staff needed to create this system.
    Recruiting the right kind of computer science specialists – in AI and data management – is critical to developing the system we have in mind.
  • Measuring and proving the ROI for customer funds invested in each system.
    Eventually, business leaders will want to see factual evidence of the return they can expect on the investments they make in this system. We must find ways to measure and prove that return.
  • Securing the major funding needed to develop a complete system
    Finally, we also must obtain the substantial funding, through several rounds of financing, that we will need to carry this project forward over a period of years, culminating in an IPO.

Feel free to ask questions!

First check our “Frequently Asked Questions” page

Progress Updates

This is a section of the website where we post news and updates about the progress regarding the project. You can find them sorted by date.

Reach Us

Are you interested to hear more about the project? Do you have an idea how to improve and/or participate in the development? Is this something that could help your business or organization? Something else?

We encourage you to send us a message.