Michelle Morris is Professor of Data Science for Food at the University of Leeds and Deputy Director of the Healthy and Sustainable Places Data Service. In this new three-part blog series, Michelle explores the role of academic-industry partnerships in driving food system change, unpacks the opportunities and limitations of consumer purchase data, and shares practical lessons for researchers seeking to build productive industry collaborations.
Interest in industry data sharing partnerships is growing rapidly, particularly as researchers seek access to new forms of data that can help address complex societal challenges.
Consumer purchase data provide one example of the enormous potential that industry collaborations can unlock. However, successful partnerships require careful planning, clear expectations and a realistic understanding of the work involved.
Based on our experience of building long-term partnerships with retailers, and drawing on insights from my recent paper with Nilani Sritharan, Group Head of Healthy and Sustainable Diets from Sainsbury’s, and some of our team members, here are some practical considerations for researchers thinking about embarking on a collaboration.
1. Start with the research question (and later a full protocol)
Before contacting a potential partner, be clear about the question you want to answer.
A retailer is much more likely to engage if you can clearly explain:
- What you want to investigate
- Why it matters
- What data might be required
- What benefit the work could deliver
A well-defined research question creates a strong foundation for everything that follows.
2. Invest in relationships
Successful partnerships are built on trust. Establish key contacts early and create effective channels of communication. Be prepared to spend time understanding your partner’s priorities, constraints and motivations.
It’s also important to consider demand management for both parties, there is an ongoing time commitment throughout collaborative research from both the data partner and the academic institution. Careful thought is needed (on both sides) about how this will be provided and maintained to ensure the success of projects.
We’ve found that partnerships work best when they are viewed as long-term relationships rather than one-off transactions.
3. Make sure you have the right expertise
Large commercial datasets are often complex and challenging to work with.
Researchers need:
- Data science expertise
- Appropriate computing infrastructure
- Subject matter expertise
- Knowledge of governance and ethics
For nutrition research, nutrition expertise is particularly important. Without appropriate context, there is a risk of drawing inaccurate conclusions.
4. Secure data infrastructure is essential
Commercial data can often contain both customer sensitivities and business sensitivities. Having a secure environment for storing and analysing data is therefore essential.
The infrastructure, governance processes and security arrangements should be established before any data are transferred.
5. Be realistic about timescales (and expect everything to take longer)
Data sharing agreements, governance approvals, legal reviews and data preparation always take longer than expected (months, sometimes even longer), so it is important to build in enough time for your project.
However, it’s important to note that there is a balance to strike, as timelines that are too long may result in findings that are no longer relevant to business priorities or the fast-moving policy landscape.
Projects involving multiple partners may require even more time, as typically no ‘one size fits all’. The time taken to establish a data sharing agreement can vary considerably from months to years. Likewise, a standardised format for sharing of retailer sales data is yet to be established, so data cleaning and preparation requirements will differ by retailer.
6. Agree milestones and expectations
Clear expectations help keep your projects on track. Work with your partner to co-produce and agree:
- Roles and responsibilities
- Key milestones
- Decision-making processes
- Communication arrangements
- Publication expectations
Co-producing these plans helps ensure they are realistic and achievable.
7. Plan dissemination from day one
Dissemination should not be an afterthought. Academic publications remain important, but researchers should also consider the following to maximise the reach and impact of the research:
- Policy briefings
- Public engagement
- Industry reports
- Media opportunities
Many commercial partners will have publication and communications review processes. Building these into project timelines from the beginning can prevent delays later.
8. Keep detailed records
Industry collaborations often involve large teams, long timelines and complex decisions. Documenting decisions, agreements and changes throughout the project can save significant time and confusion later.
Good record-keeping can often be overlooked but it can make a substantial difference to the success of your collaborations.
Final thoughts
Industry collaborations can be challenging, but they can also be incredibly rewarding.
The most successful partnerships are built on shared purpose, mutual respect and transparency. When these ingredients are present, collaborations can generate evidence that would otherwise be impossible to produce.
As researchers continue to explore new forms of smart data, building effective partnerships will become an increasingly important skill. Investing time in getting the foundations right is crucial for successful partnerships and the wider impact of the research.
Recommendations checklist for working with retailer data
Table 1 - Recommendations checklist for working with retailer data
| Recommendation | Before you start | Ongoing throughout a project |
| Consider demand management (both parties) | ✓ | ✓ |
| A secure data infrastructure for hosting data | ✓ | |
| Data Science Expertise in your team | ✓ | |
| Nutrition Expertise in your team | ✓ | |
| A clearly defined research question (and later a full protocol) | ✓ | |
| Support for legal, data acquisition, partnership management (Consider the most appropriate skill set for this support) | ✓ | ✓ |
| Realistic timeframe for each stage of the project | ✓ | |
| Project milestones and expectations | ✓ | |
| Detailed dissemination plan (including public relations sign off) | ✓ |
Article contributors and declaration of interests
- Michelle A Morris is an inventor and shareholder at Dietary Assessment Limited but has not received payment from the company to date. Michelle has worked with multiple large retailers who have shared data for research purposes.
- Nilani Sritharan and Maddie Thomas work for Sainsbury’s Plc.
- Alice Kininmonth, Emma Wilkins and Victoria Jenneson have worked with multiple large retailers who have shared data for research purposes.
*“Thanks to all participants at the Healthy and Sustainable Diets Partnership Workshop at the University of Leeds on Tuesday 18th July 2023, whose contributions are represented in this image. The workshop was funded by a University of Leeds Engaged for Impact Prize and convened in collaboration with the Leeds Consumer Data Research Centre. Artwork Scribed by NiftyFox https://www.niftyfoxcreative.com/”
