How to scale innovation via Open Innovation Procurement (OIP) platform

Inspired and based on Bill Gates Breakthrough Energy venture report

Agnieszka Zimolag
9 min readMar 19, 2020

With the climate change my wish is that innovation would be accelerated so that we can arrive at sustainable solutions faster helping to combat the bad effects of climate change and start living in a cleaner world

What if there would be a platform where business needs would be recognized and matched with skilled people who are willing to work on new projects, people who are specialized in specific areas and people who are seeking new ideas to invest in? Can innovation be more automated and more easily scalable? With the amount of data being produced these days, we can see how the builders and ideators could collaborate with more ease. Once the parties would come together they could start sending each other incentives and discuss ideas to develop new partnerships. Procurement in the innovation processes could allow for more transparency and lean/agile way that could enhance the efficiency of innovation delivery. By standardizing the key processes and combining disciplines together and setting up guidelines the innovation could be more focused, receive the resources it needs and have a more streamlined path towards the commercialization.

I like to think about innovation as a collaborative marketplace where different parties come together to make a deal and need a certain framework in order to close that deal. That’s why procurement platform seems like the best way to utilize that vision.

After reading Breakthrough Energy Executive Summary: Advancing the Landscape of Clean Energy Innovation I was even more convinced that the path towards Innovation and Renewable Energy needs a clear roadmap and current web technology could definitely help in that. The Innovation cycle needs standardization and localization at the same time.

What are the frictions in the current innovation procurement cycle?

Based on the Breakthrough Energy report

  • Securing financial support
  • Demonstrating the compatibility of new technologies with existing systems
  • Inventions that are considered by the investors are more commercially viable
  • The availability of testing facilities for product demonstration is limited by the small number of facilities suitable for sustained testing and by their specialization
  • Overview of what is the innovation landscape for the specific market sector
  • Access to the prediction models and in-depth analysis of what assets are the startup in the possession of and guidance on how to build on top of these assets

With these frictions in mind, I would like to propose a platform streamlining the innovation cycle, allowing parties to match and bid for the innovation deals and further down the road make predictions about possible next investments and keep informing users about the ongoing changes in the current landscape. It would allow the regulators, federal and local governments to set the standards and initiate reformations that would lead to a clear roadmap towards a new energy infrastructure.

The functionality of the Open Innovation Procurement platform

What is Open Innovation?

Open Innovation was defined as the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively (Henry Chesbrough, 2003)

Gassmann and Enkel, University of St. Gallen, Switzerland

Setup profile

  • Just like standardization this platform also needs localization. Universities, private industry, philanthropies, state and local governments should create local structures that will enable to build suitable solutions for the specific regions, leveraging the region’s resources and established infrastructure


  • Pulling data about the demand
  • Search for investment, a partner in testing facilities, funding, corporate partner or skilled professionals
  • Search for the compatibility within the existing landscape
  • By indicating what data you are producing there could be prediction models implemented that could tell you into which areas you should invest, what are the possible markets that you could look into to search for new ideas, with who you should collaborate to create the most value for your business.

Let’s take a look at Tesla as an example. Since they are gathering but also generating lots of data from the usage of their cars they now can focus their forces on building a self-driving fleet of cars. It seems like a very obvious direction but having predictions backed up by collected data you could drive the business forward and even automate the innovation on some level.

  • Have insight into the past collaborations of the parties you want to collaborate with and review their reputation scores


  • Ability to enter the competition to develop portfolio focused innovations
  • A formal set of major evaluation criteria — such as technical merit, market viability, compatibility, and consumer value — with specific metrics for each criterion
  • Automation of contract creation and contract analysis
  • Risk management and security
  • Dynamic price/asset prediction necessary to close the deal

Innovation management

  • “After-deal” onboarding and dynamic performance evaluation
  • Visibility over the project evolution and assets for corporate adapters, financial investors and policymakers
  • Specific portfolio structure supporting breakthrough technologies. Continuously updated long term roadmap of where possibly investors would like to place money and which would be dictated by the startups as well and where the development of renewables is heading towards
  • Ability to set up your own performance metrics and measure them against the existing landscape metrics
  • Fast-changing market conditions management
  • Proactive supply chain risk mitigation insights with recommended alternatives
  • Recognition of the procurement innovation stages and adapting its functionalities to support achieving goals specific to that stage and moving to the next one. From Concept testing -> Concept initiation -> Develop&Launch

Extra functionalities

  • Micro investments and obtaining shares from not only the investors but corporate partners that want to support your research and a solution
  • Data coming from the platform should help in identifying best practices and trends in the deployment of clean energy technologies, including financing mechanisms, consumer protections and equitable sharing of benefits among all socio-economic groups and geographic locations
  • Once the partnership is established and you would release your first outcome to the world the data should be continuously gathered in order to ensure ongoing data modelling/ prediction processes to ensure further development of breakthrough energy establishments and collaborations

Cognitive procurement

The development in the procurement services is advancing towards automating more of its repetitive tasks, which allows it to move the focus away from the transactions and toward strategy. I would like to take a step forward and ask how the procurement mechanism could enable the startups in procuring its services, products and operations faster and more efficiently. How can we think not only about disruptive businesses but also what tech and platform will allow these businesses to become even more disruptive? I like to believe that the frameworks in which we operate play a huge role in achieving success since they bring structure to the processes but also have mechanisms that enable decisions and ideas to be defined much faster.

What could be the potential benefits of cognitive procurement?

  • Liberate procurement teams from even more mundane tasks (drafting constracts, reviewing them, finalizing terms and conditions) and allocate tasks to the human that machines cannot perform. Fuel effectiveness via new efficiencies and shift the focus towards strategic thinking
  • Assist teams in grasping an increasingly complicated and disrupted innovation environment
  • Produce better results (i.e. providing new knowledge, detecting and identifying new trends and correlations, making contextual decisions and more)
  • Compare data for all benchmarking categories for the entire enterprise (it could allow for the identification of the areas worth investing in, areas of improvement as an example) and present it in a comprehensive and actionable way
  • Present the company with resources needed to close a deal
  • Present opportunities with various possible outcomes and value delivered
  • Advise which options are needed in the specific time and how do they align with the company roadmap and industry/ government roadmap

Two Key Applications of Cognitive Procurement

Intelligent Sourcing — Re-evaluating suppliers in order to achieve the greatest efficiency and value. It could help you identify suppliers that are best aligned with the company strategy and the roadmap and are ecosystem market fit. It would save on the time and resource-consuming research and manual data aggregation.

The key to the intelligent sourcing is acquiring properly synthesized data to train the machine running behind the platform. Furthermore, the qualitative aspect is as important as the quantitative one because learning from bad data will lead to poor results.

The cognitive procurement platform would use ML /AI and big data points to optimize decision-making processes throughout the entire supply chain. These decisions should be supported by the explanation that would allow humans to arrive at the right decisions thanks to the platform reasoning. That will allow people to have the final say and use that analysis to make the decisions. Making ML&AI explainable would be a key to make this platform powerful.

Intelligent Contracts—Cognitive procurement could also streamline intelligent contracts. It could pull the resources from the partnering companies, regulators, federal government, policymakers and create contracts that would be supplied to all parties that need to leave a signature. It could streamline the processes towards more efficient procurement and acquire necessary/ missing pieces of information from the relevant parties if needed. When data moves faster, the transactions can also happen faster which leads to faster deal-making.

How the adaptability and modularity of cognitive procurement could work?

Let us imagine a situation when a new innovation in the energy sector has been introduced and put into commercialization. Imagine how that naturally is disrupting the entire supply chain and creates new demands on the market. The cognitive procurement learns immediately about that innovation and starts analyzing how the supply chain is going to be affected and calculates new demands. The platform would be connected to the external sources of information (there are many providers of supply chain risk management technology that enable that) in order to gather and analyze the incoming data. How that change in the supply chain would restructure it?

  • Informs the affected parties and adjust their roadmap and innovation strategy
  • Identifies new demands and adjust their innovation path with the support of regulators, investors, local and federal governments etc.
  • Identifies necessary changes to the innovation investment portfolio structures

Summary of key actions

  • Focus on the innovation area
  • Plugin local and government innovation roadmaps
  • Attract testing facilities, investors, companies willing to innovate
  • Connect with innovation competitions, digitize the terms and conditions and define the roadmap to win the bids
  • Build procuring platform heavily focused on the advanced search and profile creation with a specific set of personalization features
  • Matching financial supporters with companies that are about to partner to innovate. Use the platform as a form of securing the credit terms
  • In-depth analytics of what the innovation landscape looks like and where the innovation is about to thrive and the company assets align with it

If you are interested in learning more about my research please check out two of my latest publications:

How quantum computing will affect Generation Z?


2030 trend report

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Disclaimer: These are the projects that I do independently in my free time out of my passion to the innovation and strategy and they are not connected to any organization and I am not collaborating with any company related to my research.