Unconventional Wisdom: How Chanakya's Statecraft Principles Can Transform Data Science Partnerships

As a data science leader, I've discovered an unconventional source of inspiration for managing partnerships: Chanakya, one of India's most renowned political scientists. The Arthashastra, his seminal work on politics, economics, and diplomacy, offers a distinctive approach to collaboration in the context of Statecraft. In this blog, I'll explore how I've adapted the four principles of Sam, Daam, Danda, and Bheda from the Arthashastra to effectively navigate data science partnerships.

Saam: Collaboration through alignment and friendship

In statecraft, Saam is used when two nations are friendly and can work together harmoniously. This represents an ideal situation when two countries are naturally inclined to cooperation.

??In the context of data science, Saam can be used in a situation where the product and data science teams share a common vision and have a good relationship.

Product Leader (PL): Our teams have great rapport; let's collaborate on a new project.

Data Science Leader (DSL): Agreed! Let's first align objectives and clarify the project scope.

PL: What's next?

DSL: We'll set up regular communication channels and checkpoints to stay aligned.

PL: Looking forward to it!

On the flip side, the risk of using Sam is the pressure to be compliant due to the friendly relationship, which may lead to overlooking potential challenges or disagreements.

Daam: Incentivizing collaboration

In statecraft, Daam is employed when two states are neutral or adversarial but share a common economic interest. In data science, Daam represents a situation where the partnering team maybe resistant to the DS team but the collaboration is incentivized by showcasing the benefits and rewards of a successful partnership.

PL: My team is hesitant to collaborate with the data science team, as they are unsure about the value it brings and its a lot of work and coordination to bring teams to work together.?

DSL: We can demonstrate the potential benefits of our collaboration by showcasing successful projects from other teams and highlighting the rewards they received.

PL: That could work. How do we ensure my team is motivated throughout the project?

DSL: We can set milestones and offer incentives for achieving them, ensuring that both teams remain engaged and motivated.

PL: Sounds promising.? I'll arrange a meeting to discuss this further.?

Daam is useful for gaining alignment quickly and incentivizing teams to work together. However, the risk of using Daam is the pressure to be overly compliant to make the team look good, which may lead to superficial collaboration. Another risk to watch out for is setting up the wrong incentives to build a partnership (Ex: Helping a product team getting more launches approved forgoing data rigor in the process.

Danda: Asserting authority to ensure compliance

In statecraft, Danda is used by a strong state to punish a misbehaving weak state. In data science, Danda represents a situation where the data science leader asserts authority to ensure collaboration and compliance from the product team.

PL: Our team is not convinced about the value of working with the data science team on this launch. Your team is raising a lot of objections but we want to go with our intuition.

?DSL: Your team would be the only team going against our recommendations across all product teams if you went for the launch. I’ll have to inform the product VP too as he has specifically asked for our team’s input in key launches.

PL: Hmm.. maybe we need to dig deeper here. I dont think your team understands the broader context.

DSL: Wish you brought this up earlier. Happy to discuss the broader context and see if it makes sense to change the DS recommendation. Let’s find a time to discuss further.

Danda is useful when the data science team has a strong reputation and senior leadership backing. The risk of using Danda is making enemies within the organization, and over time, people may try to discredit your work if you use this approach too often. Use Danda very sparingly as a last resort !

Bheda: Leveraging differences for the common good

In statecraft, Bheda is used by countries that may be weaker than two neighboring countries that are stronger. Bheda as a strategy involves using differences to achieve a common good. In data science, Bheda is about leveraging divisions or differences between teams to drive collaboration and benefit the entire organization.?

For data science teams, this is valuable approach in change management, specially when bringing a data culture to an organization. Typically, one or a few teams are all for data led decision making while others are resistant. In these situations, the partnership with the data forward teams can be highlighted in broad forums to the advantage of the data science team’s influence.

PL: Our team is feeling left out after seeing the success of another product team's collaboration with the data science team highlighted in our leadership staff meeting.

DSL: That collaboration has indeed been fruitful, and we'd be more than happy to work with your team as well. We had reached out initially but your team told us they were busy with a full roadmap and that data and insights were not really needed.?

PL: No, no. Seeing what I saw in the presentation and our VPs enthusiasm for the data driven approach , we want the same collaboration with your team. We cant be the only team not using data and insights in making product decisions.

DSL: Cool, more than happy for our teams to work together. Lets find a time to discuss further

The risk to watch out for when using Bheda is that some teams might feel undervalued or pressured to collaborate, potentially leading to resentment.

Final Thoughts

As a data science leader, I've found Chanakya's Arthashastra to be an invaluable resource for navigating partnerships. Adapting the principles of Sam, Daam, Danda, and Bheda has enabled me to manage complex team dynamics and forge successful collaborations. I'd appreciate your feedback and thoughts—please feel free to share your comments!