Tales & Tips from the Trenches: Extend the Impact of Enterprise Data through Partnerships

This quarter’s column is written by Ted Sienknecht, PMP, CISSP, who is a Principal Architect for Public-Private Partnerships (PPPs) at The MITRE Corporation. He has delivered data- and user-centric solutions for more than 20 years, drawing on his integrative leadership and analytics expertise.

Ted founded and co-leads MITRE’s PPP Community of Practice and has co-created and matured PPPs in the healthcare, financial, safety, and cybersecurity domains. His results include: $300M anti-fraud impact from one PPP, a patent for automating secure analytic environments, and multiple recognitions for partnership-driven data solutions.

A new approach to wicked problems is taking root: data-sharing partnerships that accelerate the innovation of solutions for shared problems. The example of the myriad of COVID-19 challenges shows that coordinated, data-driven action across boundaries has helped fast-track solutions such as testing, vaccines, and non-pharmaceutical interventions. In this article, we will explore how organizations can extend their concept of enterprise data – and mission impact – through data-sharing partnerships.

Too Much and Not Enough

The increasingly interconnected economy, organizations, and systems of today make it hard for any single organization to solve wicked problems by acting alone. In fact, collaboration with others – including competitors – can be necessary to address the most complex problems and community risk. Compounding this is the seemingly contradictory issue of being overwhelmed with too much data, yet never having enough of the right data. Further, the siloed nature of many datasets, and the limits of even enterprise-wide repositories (e.g., data warehouses, data lakes) means that go-it-alone approaches are often limited in their impact.

Partnership-driven approaches work when the problem is bigger than what a single entity can see or control and when the problem requires collaboration to solve, such as data fusion and analysis across multiple partners’ data and perspectives. With the partnership identifying the right actionable data and then sharing in near real-time, wicked problems can be addressed over and over again, even as they morph and reappear.

A Possible Solution: Data-Sharing Partnerships

We have found that leading organizations are increasingly using data-sharing, multi-party collaboratives – such as consortia, public-private partnerships (PPPs), and information sharing and analysis centers (ISACs) – to gain insights that would otherwise not be possible. These leaders recognize the need to combine diverse data and viewpoints to inform decisions that advance their interests. Given that data is the fuel powering much of today’s economic value creation, it is not surprising that leaders are partnering to advance their respective (and shared) goals through innovative, mutually beneficial analytic solutions. These data-sharing PPPs involve collaboration among the right set of stakeholders – such as within-sector and cross-sector peers in industry; federal, state, or local governments; academia; associations; and nonprofits – to achieve their shared goal.

Applying PPPs for Impact

We have seen data-sharing PPPs deliver impact in areas such as:

The Core of Data-Sharing PPPs

Data-sharing PPPs involve multi-party collaboration around information sharing and analysis to take action on complex problems without boundaries. These PPPs are predicated on shared decision-making, shared resourcing, and shared benefit to the partners and the public. Unpacking this definition a bit…

  • Common mission – Partners are driven by a sense of urgency and the realization that their own interests are served by working together on a shared goal.
  • Collaborative working relationship – Fundamentally, the engagement among partners is both strategic and action-oriented. It involves ongoing communication, information sharing and analysis to deliver tangible results. This is not a traditional contractual arrangement.
  • Shared decision-making – PPPs embody the principle of self-governance and collaborative decision-making. The founding documents (e.g., charter, bylaws, legal agreements) codify how the partnership addresses questions such as how decisions are made, conditions under which data and results may be shared, etc. Partners generally retain the right to self-govern.
  • Shared resourcing – Successful PPPs clarify expected partner roles and contributions to ensure fairness in resourcing the PPP to achieve its mission. Contributions include funding (via e.g., membership fees, subscriptions, buying specific products or services) and/or in-kind contributions (e.g., sharing data, staff time and expertise, IT and other capabilities).
  • Shared benefit to partners and the public – Impactful PPPs deliver each partner a tangible return on their investment/contribution as well as a measurable public benefit. Given participation in PPPs is voluntary, answering, “What benefits will I gain in return for my contributions?” with a clear value proposition is critical to build and sustain the PPP. Further, the collaborative efforts of the partners through the PPP results in public benefit (e.g., safer world, economic growth, informed citizens).

Benefits to Participants

By sharing information that reflects the breadth of partners’ experiences and drawing on the power of their network, PPPs by definition provide a more comprehensive solution. This kind of trust-based collaboration can often detect signals in the pooled data that would not be feasible in smaller or partner-specific datasets. All of this creates profound value for partners by enabling them to take meaningful action on the results PPPs share on an accelerated timeline (sometimes near real-time). Partners also benefit from establishing new relationships and expanding their networks from conversations around the information sharing and analysis.

Lessons Learned for Data Leaders

Looking across the dozens of data-sharing partnerships we have shaped, facilitated, or operated as a trusted third party, we found that successful PPPs require leaders and experts from each data-providing entity to negotiate expectations for data sharing and collaboratively shape the specific operational concept for analysis.

Initially, leaders must work together to clarify the purpose and “business deal” of the PPP, and then identify and resolve specific issues. An anti-fraud PPP serves as a good example of how to facilitate the multiparty negotiations and resulting legal agreements. By considering how each potential partner must assess their own internal legal, privacy, security, and IT risks to secure approval to share data, the trusted third party was able to proactively shape the discussions for success, covering topics such as:

  • Use and ownership of intellectual property and other rights in data
  • Data protection expectations including security, privacy, and permitted uses
  • Conflicts of interest, and as applicable, role of independent trusted third party
  • Precluding unfair competitive advantage and antitrust/anti-competitive concerns
  • Liability, warranty, and other risk management topics.

Regarding shaping the partnership’s concept of operations, a safety-focused PPP serves as an exemplar. Leaders started with the end in mind and considered how partners needed to collaborate throughout the data and analytic lifecycle illustrated below.

Click to view larger

By optimizing the needed systems and methods based on goals and resourcing, the resulting set of capabilities was not only able to address partners’ current data analysis needs, but more readily respond to emergent needs.

Leaders must co-define with partners and the trusted third party the data sharing and analysis concept of operations, prioritizing and defining specific solutions for the relevant topics shown above. Even though this illustration simplifies the activities and appears linear, we have found that PPPs with a data sharing and analysis focus often benefit from an iterative or agile approach. That approach can provide value sooner to partners and foster greater co-discovery and innovation.

We have also seen that data-sharing PPPs can be tailored to fit in a range of timescales and budgets, though are non-trivial to shape and stand up. When they are well-suited to the problem, we have found that data-sharing PPPs have proven successful in multiple cases – results show that organizations can substantially increase the value of their data when specific data is combined with other partners’ data in a data-sharing PPP.

Copyright © 2021 The MITRE Corporation. All Rights Reserved. Approved for Public Release; Distribution Unlimited. 20-02595-8.

Share this post

Bonnie O'Neil

Bonnie O'Neil

Bonnie O'Neil is a Principal Computer Scientist at the MITRE Corporation, and is internationally recognized on all phases of data architecture including data quality, business metadata, and governance. She is a regular speaker at many conferences and has also been a workshop leader at the Meta Data/DAMA Conference, and others; she was the keynote speaker at a conference on Data Quality in South Africa. She has been involved in strategic data management projects in both Fortune 500 companies and government agencies, and her expertise includes specialized skills such as data profiling and semantic data integration. She is the author of three books including Business Metadata (2007) and over 40 articles and technical white papers.

scroll to top
We use technologies such as cookies to understand how you use our site and to provide a better user experience. This includes personalizing content, using analytics and improving site operations. We may share your information about your use of our site with third parties in accordance with our Privacy Policy. You can change your cookie settings as described here at any time, but parts of our site may not function correctly without them. By continuing to use our site, you agree that we can save cookies on your device, unless you have disabled cookies.
I Accept