Letting Data Engineers and Data Scientists Roaming Free in Strategic Planning.

Lately, I have attended several data meetups in Asia, and I have observed a problematic situation. Many upper management are letting engineers and technical people run the company’s technical strategy. This scenario is understandable as many upper managers need to gain new data technical skills and must rely on technical people for the issue. The problem is most, but not all, technical people at this level still need to gain business strategy skills. While their knowledge is definitely crucial as input for upper management strategy planning, letting them make strategic decisions is usually a recipe for failed data-driven transformation.

In today’s data-centric business world, the integration of technical expertise into strategic planning is crucial. However, a persistent issue that many organizations face is the need for more data technical skills among upper management. This gap often leads to engineers being given free rein to plan strategy and manage technical operations. While their technical understanding is invaluable, their initiatives might only sometimes align with the company’s strategic goals. This article examines the consequences of this misalignment and proposes strategies to ensure that technical management and company strategy are in harmony.

The Technical Skills Gap in Upper Management

Hopefully, the upper management is typically well-versed in strategic vision, financial oversight, and leadership. However, the rapid evolution of data technology has left some senior executives needing more technical proficiency to understand and guide data-driven initiatives fully. This skills gap can lead to several problems:

1. Limited Vision for Data Utilization: Without a deep understanding of data capabilities, upper management may not see the full potential of data initiatives, leading to underinvestment or misaligned projects.
2. Communication Challenges: The lack of technical language and understanding can create significant communication barriers between upper management and technical teams, resulting in strategic misalignments.
 3. Resistance to Technological Change: Executives who are not comfortable with data technology may resist or undervalue innovative data-driven strategies, potentially stifling growth and innovation.

Engineers Roaming Free in Strategy Planning

Engineers, with their technical expertise, play a crucial role in implementing and managing technological solutions. However, when they are given free rein to plan and manage strategy independently, several challenges can arise:

1. Strategic Misalignment: Engineers may prioritize technically advanced solutions that do not necessarily align with the company’s broader strategic objectives, leading to resource misallocation.
2. Isolation from Business Context: When technical teams operate in silos, they might focus on immediate technical challenges without considering the larger business context, resulting in initiatives that lack strategic relevance.
3. Imbalance in Priorities: Engineers may emphasize technical perfection and innovation over commercial viability and strategic impact, leading to projects that do not contribute effectively to the company’s overall goals.

What can go wrong if you let them play too much?

Here are four reasons why data engineers and data scientists should not be the primary strategists:

1. Lack of a Broader Business Perspective

Data engineers and data scientists are typically focused on technical excellence and innovation. Their training and day-to-day responsibilities revolve around data manipulation, analysis, and implementation of technical solutions. While they are experts in their field, they may not have the necessary experience or perspective to fully understand the broader business landscape, including market dynamics, customer needs, competitive pressures, and financial considerations.

• Strategic Misalignment: Their strategies might emphasize technical innovation without considering market viability, customer impact, or long-term business sustainability.

2. Imbalance in Prioritization

Technical professionals often prioritize projects based on technical merit and innovation potential. While these factors are important, they do not always align with the company’s strategic priorities, which may include financial performance, market expansion, customer satisfaction, and operational efficiency.

• Resource Misallocation: Technical teams might allocate resources to technically impressive projects that do not contribute significantly to the company’s strategic goals, leading to inefficient use of resources.

3. Siloed Decision-Making

Data engineers and data scientists usually operate within the confines of their technical departments. This siloed approach can result in decision-making that does not take into account the interdependencies between various business functions such as marketing, sales, finance, and operations.

• Lack of Cross-Functional Integration: Effective business strategy requires a holistic approach that integrates insights and requirements from all business areas, something that data engineers and data scientists might overlook when working in isolation.

4. Communication Gaps with Executive Leadership

Effective strategy formulation requires seamless communication and collaboration with executive leadership and other key stakeholders. Data engineers and data scientists might lack the necessary skills or experience to effectively communicate complex technical insights in a way that aligns with business objectives and resonates with non-technical stakeholders.

• Ineffective Strategic Communication: Miscommunication can lead to misunderstandings, misaligned expectations, and, ultimately, strategies that are not fully endorsed or supported by the executive leadership and other critical parts of the organization.Bridging the Gap: Strategies for Alignment

To address these challenges, companies need to foster better alignment between technical initiatives and strategic goals. Here are some key strategies:

1. Integrated Planning Processes: Develop integrated planning processes that involve both upper management and technical teams. This practice ensures that strategic objectives and technical capabilities are considered together, promoting coherence and alignment.
2. Technical Training for Executives: Provide upper management with ongoing education in data science, analytics, and technology. This training will help bridge the knowledge gap, enable executives to make informed decisions and support data-driven initiatives.
3. Strategic Oversight Committees: Establish committees that include both senior executives and engineers to review and guide technical strategies. These committees can ensure that technical projects align with the company’s strategic objectives.
 4. Enhanced Communication Channels: Develop robust communication channels between upper management and technical teams. Regular joint meetings, workshops, and transparent reporting practices can help align efforts and goals.
5. Balanced Key Performance Indicators (KPIs): Implement KPIs that reflect both strategic objectives and technical achievements. This balanced approach ensures that technical teams align their projects with the broader business strategy, ensuring mutual accountability.

Conclusion

Many organizations have successfully bridged this gap through innovative practices. For instance, Amazon’s two-pizza team structure ensures that small, cross-functional teams work on projects with clear strategic goals. This approach fosters alignment between technical initiatives and business objectives. Similarly, IBM’s emphasis on continuous learning for executives includes technical training, ensuring that their leadership is well-versed in data and technology.

The lack of data technical skills among upper management presents significant challenges, especially when engineers are given free rein to plan strategy and manage technical operations. By fostering collaboration, enhancing technical literacy among executives, and integrating strategic oversight, organizations can bridge this gap. This approach ensures that technical initiatives not only excel in execution but also align with broader business objectives, driving sustainable success in a data-driven world. Recognizing and leveraging the strengths of both upper management and technical teams is crucial for navigating the complexities of modern business and achieving strategic alignment.