Harmonising Executive Strategy and Dynamic Data Analytics: A 6-Step Framework

Are top-down strategies and swift data analytics projects at odds with one another?

Would you trust a dentist that doesn't use a mirror to examine or operate on you? Then you should not rely on strategies that do not dynamically evolve based on feedback from data analytics projects.

In this article, I will touch on the downsides of top-bottom strategies, explain the advantages of swift analytics projects as well as provide an example of how to supercharge strategies through an integrated top-bottom & bottom-top approach.

At least 90% of all strategies remain in an dusty shelf. If you want to avoid strategising from an ivory tower, this article is for you.

Downsides of Top-Down Strategies

1)Long Implementation Time

Top-down strategies often involve detailed planning and analysis at the beginning. This can lead to longer implementation times as all aspects of the project are thoroughly considered before any development begins.

2) Rigidity

Top-down approaches may be more rigid, making it challenging to adapt to changing requirements or market conditions during the project. This can be a significant drawback in fast-paced environments.

3)High Initial Investment

Top-down strategies may require a substantial upfront investment in planning and design before any tangible outcomes are realised. This can be a decision-making burden and a risk if the project faces unexpected challenges or changes.

4) Potential Misalignment with User Needs

In a top-down approach, decisions often come from upper management without significant input from lower-level employees or end-users. This can result in solutions that do not align well with actual user needs.

How Quick Data Projects Can Help

1) Agility

Quick data projects, allow for faster adaptation to changing requirements. This can mitigate the rigidity associated with top-down strategies.

2) More Efficient Iterative Development

Quick data projects often follow an iterative development process, allowing for continuous improvement based on feedback. This helps in addressing issues early and ensures that the final product better meets user expectations.

3) Reduced Risk

By delivering smaller, incremental results more frequently, quick data projects can help manage risk more effectively. It becomes easier to identify and address issues early in the development process.

4) Stakeholder Involvement

Quick data projects often involve more collaboration and input from various stakeholders throughout the development process. This ensures that the final product aligns closely with user needs and expectations.

5)Faster Time-to-Value

Quick data projects aim to deliver tangible results rapidly, providing value to the organisation sooner. This contrasts with the longer timeframes often associated with top-down strategies.

So how do you integrate the two approaches together? There's no one size fits all and its up to you to decide the best way to supercharge your existing methodology.

Here's a simple example of how to achieve an Integrated Strategic Approach

1. Define Organisational Goals
2. Conduct Swift Analytics projects to assess risk, financial performance, operational efficiencies, etc.
3. Integrate project outcomes into a SWOT analysis to align organisational needs with evidence-based goals.
4. Determine the necessary information to meet the objectives.
5. Identify suitable swift data projects to gather this information.
6. Iterate through steps 2 to 5 for continuous improvement.

Summary

The article argues in favour of dynamic strategies informed by real-time data feedback. It critiques top-down approaches for their rigidity and slow adaptation and explains the agility and real-time stakeholder involvement swift data projects can add. An example of an integrated approach is provided.

Do you know anyone specialising in swift data analytics projects?