Data-Driven Decision-Making

Erik Burckart
Blog Post
February 2, 2024
Data-Driven Decision-Making
AI & Data

Five Investments to Make to Enable Data-Driven Decision-Making

Organizations today are experiencing unprecedented connectivity and generating vast amounts of data. In this era of digital transformation, the surge in data volume demands a strategic response, compelling organizations to embrace a culture of data-driven decision-making. The imperative to adapt to this digital landscape underscores the pivotal role of investments in leveraging data as a valuable asset. As businesses navigate this evolution, the ability to harness and interpret data becomes not only a competitive advantage but a fundamental driver of informed and impactful decision-making.

By effectively utilizing data to inform decision-making, an organization can improve its operational efficiency, create alignment with their customer base, mitigate potential risks and uncover competitive advantages required for sustainable growth. Achieving these results is not a quick process and requires a significant organizational investment in several key areas:

1. Planning

Developing and implementing a plan to achieve data excellence is a significant first step that sets high-performing organizations apart from their competitors. A successful plan aligns data initiatives with business objectives, creating strategic alignment throughout the organization. In the planning process, it is important to identify and allocate existing resources by evaluating current processes. This will help organizations determine the need for additional investments to effectively implement and support the data program. Establishing measurable goals and key performance indicators will help track results and identify real-time adjustments to inform the program.    

2. Data Governance

Technology-enabled organizations have a responsibility for effective data governance. Having an established and robust data governance policy is a must and ensures organizational data quality, security and compliance. This includes having a clear definition of internal roles and responsibilities around data management and identifying areas that require an investment to implement the proper tools, professionals or technologies required to maintain and facilitate effective data governance.  

3. Analytics and AI

Investing in advanced analytics and artificial intelligence tools is necessary in today’s data landscape, helping uncover important data insights that inform pivotal real-time business decisions. The use of predictive analytics helps set expectations for the business through historical data and forecasting, with machine learning algorithms quickly identifying data patterns, trends and correlations that human analysis may overlook. Embracing and investing in AI is a necessary step for organizations to succeed in today’s digital age by identifying new and increased revenue opportunities.

4. Employee Training and Change Management

Empower existing employees by offering a comprehensive training program highlighting the necessary skills to properly interpret and leverage company data. This shows existing employees that the company is investing in their success and simultaneously enhances data literacy throughout the organization. The creation and implementation of proactive change management strategies signifies a unified approach within the company that creates a culture of preparation, support and assistance during the transition to a data-driven organization.

5. Continuous Improvement

Embracing a culture of continuous improvement and education establishes the importance and prioritization of effective data management in the organization. Regularly assessing and updating data programs will ensure they remain aligned with the evolving business objectives and technological advancements of the company. It is important that newly adopted systems can seamlessly integrate with the existing analytical and machine learning environments, establishing a cohesive and comprehensive approach to data utilization.  

Being proactive in identifying new strategies that can refine and enhance company data is an important step, too. This includes the identification of additional data processing techniques, implementing additional quality control measures and utilizing additional technologies to increase data accuracy. Prioritizing these initiatives gives an organization the flexibility to evolve and pivot with changing market dynamics and maximizes the impact of data resources.

Notable Improvements Observed in a Data-Driven Organization

The shift towards data-driven decision-making is no longer a luxury, but a necessity for organizations looking to sustain success. This investment empowers businesses to effectively navigate challenges and creates significant improvements across the organization, including:  

1. Establishing a Competitive Edge

Data-driven decision-making enables businesses to identify market trends, uncover customer preferences and action emerging opportunities faster and more accurately than their competitors, uncovering new revenue opportunities and positively impacting the organization’s bottom line.  

2. Increasing Operational Efficiency

With the investment and implementation of data platforms and machine learning tools, companies can identify bottlenecks in their processes and action them in real-time, enhancing their overall efficiency. This uncovers cost saving opportunities through the effective allocation of existing employees and resources, creating a more agile organizational structure.  

3. Developing a Customer-Centric Approach

Data-driven decision-making allows organizations to gain deeper insights into their customer base. Increased insights around specific consumer habits, preferences and behaviors create new opportunities for personalized and targeted marketing strategies. The adoption of these strategies leads to improved customer satisfaction, trust and loyalty by allowing the company to action direct feedback in real-time.  

4. Performing Risk Mitigation

The implementation of data analytics and AI tools helps identify potential risks in real-time, enabling companies to proactively address them before they escalate. This not only protects the business from legal compliance issues, but also allows them to proactively address market fluctuations and customer demands. This builds trust and resilience among key stakeholders and creates confidence in their decision-making in the face of uncertainty.

Moving towards becoming a data-driven organization takes specific investments but will lead to significant improvements across the company. At BUILT, we utilize our Data Level Up program and start with a comprehensive assessment of an organization’s current data infrastructure, capabilities and the alignment of data with business goals. We then build a roadmap for maturing in key areas that will grow the data program.

If you are ready to embark on the journey to data-driven decision-making, contact us today: www.builtglobal.com/contact.

About the author, Erik Burckart, Partner at BUILT and Head of Strategic Initiatives: Erik is an experienced entrepreneur, executive, technologist and business strategist. He has delivered valuable technology solutions across insurance, retail, logistics, healthcare, telecommunications and pharmaceuticals. Erik has over 100 issued patents and won Triangle Business Journal's CIO of the Year for Innovation & Transformation.

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