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Balancing Value with Time to market when innovating

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Warning: This post is a long rantof reflections. I wrote it mainly togain personal clarity. I published it because believe it would be of interest to others.

I am currently leading a rapid innovation project with theEuropean division of a global Fortune 20 firm.

The project is focused on solving a problem area using data. Specifically the customer wants to answer questions such as:

• How are we tracking compared to the market?

• How are we doing compared to our competitors?

• Why and what to do about it?! This is the big one.

    • Based on the numbers, what dare the underlying reasons and drivers for our performance?
    • What should we do about it?
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    As with any innovation the goal is to drive to business value. The faster the better.

    It is the goal, set by me as the Project Lead, that this innovation initiative becomes an absolute “no-brainer” with regards to implementing the solution.

    I want the Executive sponsor to go:” Let’s do it!’ immediately after having seen the innovation! From an ROI perspective I want it to return no less than 10x over 3 years.

    As we are executing the project we must continuously balance between Total Business Value created vs Time To Market.

    Balancing Value with Time to market

    In the context of ROI, i. e. balancing Time with Value, a few levers can be adjusted:

    Value Levers

    • Increase the number of users directly engaging and using the solution so as to increase the total value of the solution. Challenge: with more users being designed for tie complexity in creases and we potentially risk designing a “meh” product for many vs a “wow” product for one user group. With the addition of users the time to realize also dramatically increases. Implementation and adoption becomes harder.

    • Serve higher value users / increase the value of insights generated. One way to potentially do this would be to extend usage of this product to the actual Board-members and CxOs. Today the board- members all benefit indirectly as some of the insights are shared with them, but lagging and with less nuance and depth.

    • Enable platform usage + ecosystem of the data. This builds on the previous point and extends the direct usage to the ecosystem. For my customer this would be an extraordinarily good use case due to their global presence. With such an ambition there would clearly be challenges. It would likely significantly delay realization as architecture and API’s would become higher priorities. Additionally to take advantage of this platform, the customer would need to enable a number of new capabilities. As a vision this piece might be really interesting however.

    Time to market

    Another idea would be to focus wholeheartedly on speed to market. We would launch something MUCH quicker and realize incremental but notable value. I would ensure that we had a strong understanding of the value drives and the vision up-front.

    Conclusion

    Every project is different in its own ways, this one included. This one is particularly tricky as we are running to a tight deadline for release (aiming for early August), much of the project is being done virtually due to resource challenges, and lastly: The availability of stakeholders for our Design workshop is limited.

    For now my gut feel, based on the data we have today, is to seek to:

    • elevate the value of the solution by designing it so that the B. o. D ‘s will use it, all while

    • seeking to launch an MVP for our primary user as fast as possible) and then iterate from there.

    Benefits to this approach will be

    • Momentum + early wins. Momentum is one of the top parameters I try to optimize for when innovating with large enterprises. It is absolutely crucial to nurturing a culture of innovation and supporting my innovation-champions.

    I define innovation momentum as: “Making progress towards adoption of something that is of clear and tangible business value.”

    Benefits of momentum, not previously mentioned:

    • It lowers commercial risk for both my company + my customer,
    • It builds credibility with our Sponsors, and they in turn gain internal credibility
    • It optimizes for many of the typical constraints, which are very evident in this project:
      • Accessibility and time with users and stakeholders
      • Specialist resources, such as ML, Data Scientist, and other technical resource

    What will be particularly important, as with any perceived higher risk project, is to maintain my strong report with the Executive + the project owner from the customer.Luckily I have a great baseline and I expect this to be manageable. I will obviously bring them into solutioning of the best path forward, but the above represents my current Point of view.