In an era where data has become the backbone of business success, it’s baffling to see how many organizations still struggle to recognize the value of a robust data strategy.
In this article I want to dive into my thoughts on the topic: is data strategy overlooked and undervalued?
I’ll explore the reasons behind this oversight and the potential consequences for companies that fail to adapt.
More importantly, I will shed light on the significance of data strategy in driving smarter decisions, fueling growth, and ultimately, securing a competitive edge in today’s rapidly evolving, data-driven market.
The Problem with Undervaluing Data Strategy
Many organizations view data strategy as a technical issue, rather than a strategic one.
They focus on the technical implementation of data management and governance, but fail to align their data strategy with their overall business strategy. As a result, their data strategy documents may sit unused, with little practical implementation.
This is a missed opportunity. When data strategy is not aligned with business strategy, businesses may miss out on important insights, leading to lost revenue and decreased efficiency. Moreover, failing to prioritize data strategy can leave businesses vulnerable to compliance issues, cyber threats, and other risks.
But why is data strategy overlooked and undervalued?
It could be that many businesses simply don’t understand the importance of data strategy in driving business value. Alternatively, data strategy may be seen as a “nice to have” rather than a critical component of overall business strategy.
Either way, it’s clear that there is a gap that needs to be bridged if businesses want to fully leverage the power of data to drive growth and innovation.
In the next sections, we’ll explore some potential solutions to this problem, and the role of formal qualifications in advancing the field of data strategy.
The Role of Formal Qualifications in Data Strategy
One reason that data strategy may be undervalued is the lack of formal qualifications in the field. While there are plenty of technical certifications related to data management and analysis, there are relatively few formal qualifications that focus specifically on data strategy.
I have a routinely updated post on reviewing the best data strategy courses you can find online – apart from a great certification from Berkeley Executive Education, there is very little in the realm of valuable qualifications prospective data leaders and data strategists can undertake.
This can be problematic for a number of reasons.
First, it can make it difficult for businesses to identify qualified candidates who have the necessary skills and experience to lead data strategy initiatives.
Second, it can perpetuate the idea that data strategy is a technical issue rather than a strategic one, since there are few formal qualifications that recognize the importance of aligning data strategy with business strategy.
The Benefits of Prioritizing Data Strategy
When businesses prioritize data strategy, they can unlock a host of benefits that can help them achieve their objectives. For example:
- Improved decision-making: By aligning data strategy with business strategy, businesses can gain a better understanding of their data and use it to inform decision-making. This can help to identify new opportunities, optimize processes, and reduce risks.
- Increased agility: Data can provide real-time insights that allow businesses to quickly adapt to changing market conditions and customer needs. By prioritizing data strategy, businesses can create a more agile and responsive organization.
- Better customer experiences: By leveraging customer data, businesses can gain a deeper understanding of their customers and create more personalized and targeted experiences. This can lead to increased customer loyalty and advocacy.
- Reduced costs: By optimizing processes and identifying inefficiencies, businesses can use data to reduce costs and improve their bottom line.
- Better compliance: By aligning data strategy with compliance requirements, businesses can reduce their risk of regulatory violations and protect sensitive data.
Overcoming the Challenges
While prioritizing data strategy can provide a host of benefits, there are also some challenges that businesses may face when implementing it. Here are some of the key challenges, along with some strategies for overcoming them:
Resistance to change: Implementing a data strategy can require significant changes to processes, roles, and responsibilities, which can be met with resistance from employees.
To overcome this challenge, businesses can focus on building a culture of data-driven decision-making and communication, and provide employees with the training and resources they need to succeed.
Data silos: In many organizations, data is stored in silos that make it difficult to access and integrate.
To overcome this challenge, businesses can focus on implementing a data architecture that facilitates sharing and collaboration across departments, and invest in technologies like data warehouses and data lakes.
Lack of resources: Implementing a data strategy can require significant resources, including time, money, and expertise.
To overcome this challenge, businesses can focus on building a business case for data strategy that demonstrates its value and potential ROI, and prioritize investments in data-related technologies and talent.
Data privacy and security: With the rise of data breaches and privacy regulations, businesses must ensure that their data strategy aligns with best practices for data privacy and security.
To overcome this challenge, businesses can focus on implementing strong data governance frameworks that ensure compliance with regulations, and invest in technologies like encryption and access controls.
By addressing these challenges head-on and focusing on building a strong data strategy, businesses can create a more data-driven organization that is better positioned to achieve its objectives.
Where to From Here?
As businesses increasingly recognize the importance of data strategy, there are a few key steps that they can take to continue to advance in this area:
Invest in formal data strategy qualifications: As the importance of data strategy continues to grow, it’s likely that we’ll start to see more formal qualifications in this area. By investing in these qualifications and ensuring that their employees have the necessary skills and expertise, businesses can position themselves to be leaders in the data-driven economy.
Prioritize data governance: While developing a data strategy is an important first step, it’s also essential for businesses to prioritize data governance. This involves establishing a framework for managing data that ensures that it is accurate, secure, and compliant with relevant regulations.
Continuously monitor and evaluate data strategy: As with any strategic initiative, it’s important for businesses to continuously monitor and evaluate their data strategy to ensure that it is achieving its intended goals. By regularly assessing the effectiveness of their data strategy and making adjustments to their roadmap as necessary, businesses can ensure that they are staying ahead of the curve.
By taking these steps and continuing to prioritize data strategy, businesses can create a more data-driven organization that is well-positioned to succeed in today’s rapidly changing business landscape.
Closing Thoughts
Data strategy is a critical component of modern business strategy that is all too often overlooked or undervalued. By failing to prioritize data strategy, businesses can miss out on important insights, increased agility, and other benefits that can help them achieve their objectives.
However, by recognizing the importance of data strategy, pursuing formal qualifications, and aligning data strategy with business objectives, businesses can create a more data-driven organization that is better positioned to achieve success in today’s competitive landscape. It’s time for businesses to recognize the value of data strategy and start treating it as a strategic priority.
Justin is a full-time data leadership professional and a part-time blogger.
When he’s not writing articles for Data Driven Daily, Justin is a Head of Data Strategy at a large financial institution.
He has over 12 years’ experience in Banking and Financial Services, during which he has led large data engineering and business intelligence teams, managed cloud migration programs, and spearheaded regulatory change initiatives.