You're at odds with stakeholders on data analytics strategies. How do you align for operational success?

When it comes to data analytics, aligning with stakeholders is pivotal for operational success. Imagine you're facing discord with them regarding the strategies to be implemented. It's a common scenario in operations research, where data-driven decision-making is the cornerstone of efficiency and effectiveness. The key is to find common ground, ensuring that all parties understand the value of the proposed analytics approach and how it ties into the overarching goals of the organization.

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1 Understand Needs

To align on data analytics strategies, start by understanding the unique needs and concerns of your stakeholders. Dive deep into their goals, pain points, and the outcomes they expect from data analytics. This empathetic approach allows you to tailor your communication and proposals, ensuring that stakeholders feel heard and their requirements are addressed. By demonstrating how data analytics can solve their specific problems, you build trust and pave the way for collaborative strategy development.

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Tim Loomas MBA, DBA

Evidence-Based & Data-Informed | Analytics Leader | Data Strategist | Mentor & Coach
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Gaining a thorough understanding of the stakeholder's goals is the best way to prevent misalignment in the first place. However, should you find yourself in this situation, it is important to avoid casting the issue in binary terms (right/wrong, my way/highway). In short, find an "and" solution not an "or" solution. It may mean extra work for you, or it may push you out of your comfort zone, but seeking innovative solutions will only improve your process.

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Daniel Mugambi

Strategy | Project Management | People Analytics | Data Science
(edited)
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You need to engage your stakeholders' and understand their perspectives and specific concerns. To gain their buy-in, communicate your approach clearly and where possible, provide proof of concept to demonstrate quick wins. Additionally you would need to develop a collaborative plan with defined objectives while making use of regular check-ins to reinforce teamwork, celebrate successes, and adapt the strategy based on feedback and evolving business needs. To ensure impactful outcomes and build trust, continuously monitor key performance indicators, ensuring alignment with your strategic goals.

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2 Communicate Value

Effective communication of the value of data analytics is essential to win stakeholder buy-in. Explain how data-driven insights can lead to better decision-making, optimized processes, and a competitive edge. Use relatable examples and clear language to demystify complex analytics concepts. Remember, your goal is to highlight the tangible benefits that resonate with stakeholders' interests, such as cost savings, revenue growth, or enhanced customer satisfaction.

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3 Involve Stakeholders

Involving stakeholders in the data analytics process fosters a sense of ownership and commitment. Invite them to participate in brainstorming sessions and strategy meetings. This collaborative approach not only leverages diverse perspectives for more robust strategies but also helps stakeholders understand the intricacies of analytics. Their input can reveal valuable insights that might otherwise be overlooked, leading to more effective and inclusive analytics solutions.

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4 Offer Training

Sometimes, resistance to data analytics strategies stems from a lack of understanding. Offering training and educational resources can empower stakeholders with the knowledge they need to appreciate the value of data analytics. Tailor training sessions to various levels of expertise, ensuring everyone from executives to frontline employees can grasp the concepts relevant to their roles. Education is a powerful tool to bridge gaps and align everyone towards a common analytical vision.

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5 Pilot Programs

Implementing pilot programs is a tactical way to demonstrate the potential of data analytics strategies. Select a small, controlled project where the impact of analytics can be clearly observed. This real-world application provides stakeholders with concrete evidence of how data analytics can improve operations. Success in a pilot program often serves as a persuasive argument for rolling out strategies on a larger scale.

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Jose Ramirez, PhD, Colonel (ret), CAP-X, PMP

Vice President, Government Services at OptTek Systems, Inc. | PhD, Data Science & Analytics Expert | Strategic Advisor | Operations Research Expert
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I absolutely agree that pilot programs are great for showing stakeholders what data analytics can do, like a little "sneak peek" before committing to the full "motion picture." But sometimes, the real magic happens when you get stakeholders involved in the data journey before the pilot even starts. For example, instead of just showing them results, you invite them to brainstorm the project, even help pick the metrics to track. This way, they feel ownership over the process, and they're more likely to root for its success. Getting stakeholder inputs early on can actually make your analytics strategy even better.

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6 Review & Adapt

Lastly, be prepared to review and adapt your data analytics strategies based on stakeholder feedback and operational outcomes. Continuous improvement is a fundamental principle in operations research. By regularly assessing the effectiveness of your analytics approaches and making adjustments, you show stakeholders that their input is valued and that the strategies are evolving to meet the organization's changing needs.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Maikel V.

Manager, Data-Driven Transformation @ SES
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Your end customer will always want to see immediate results, which might conflict with the ideal solution for the overall organisation. Getting a clear understanding of requirements and comparing them to what is long term the best outcome is key to being able to break it down for your stakeholders and keep them engaged, even if the solution you are delivering is not 100% what the end user had in mind.

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You're at odds with stakeholders on data analytics strategies. How do you align for operational success?

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2

3

4

5

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7

1 Understand Needs

2 Communicate Value

3 Involve Stakeholders

4 Offer Training

5 Pilot Programs

6 Review & Adapt

7 Here’s what else to consider

Operations Research

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You're at odds with stakeholders on data analytics strategies. How do you align for operational success?

1

2

3

4

5

6

7

1 Understand Needs

2 Communicate Value

3 Involve Stakeholders

4 Offer Training

5 Pilot Programs

6 Review & Adapt

7 Here’s what else to consider

Operations Research

Rate this article

Thanks for your feedback

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