Data is the new currency, and how a company handles its information is critical to its success—or failure.
Ben DeBow, founder and CEO at Fortified Data, a Fort Mill, South Carolina-based provider of database managed services and database maintenance, has some ideas on how to do it best. The author of End of Abundance in Tech: How IT Leaders Can Find Efficiencies to Drive Business Value, DeBow spoke with StrategicCIO360 about why it’s important to spend time on life-cycle management, how to reduce tech costs and where future data opportunities lie.
In an era where companies have more data at their disposal than ever before—spanning their business operations, clients, research and more—what strategies are being employed to effectively analyze this trove of information and unlock its inherent value?
Companies today employ various strategies to better manage, analyze and act on their data. One key approach is the implementation of advanced analytics techniques like machine learning and artificial intelligence, which unveil patterns, trends and insights within the data. This enables businesses to extract valuable information for data-driven decision-making for both the business and technology teams.
Additionally, companies invest in robust data management systems and technologies for efficient storage, processing and retrieval. This includes data warehouses, data lakes and cloud-based platforms capable of handling large-scale and complex datasets.
Moreover, organizations prioritize data governance practices to ensure data quality, integrity and compliance with privacy regulations. By adopting these strategies, companies can leverage data to drive innovation, enhance operational efficiency and gain a competitive edge.
Another important aspect is data lifecycle management, which involves categorizing data based on its value and relevance to the business. By utilizing mature data governance and classification systems, organizations can differentiate valuable data from low or no-value data. This allows them to prioritize the analysis and utilization of high-value data while efficiently managing and disposing of data that offers limited or no business value.
This approach optimizes data storage, reduces costs and ensures that analyzed data is of the highest quality and relevance. By combining effective data analysis strategies with data lifecycle management, companies can unlock the true value and potential of their data resources, make informed decisions based on meaningful insights and stay ahead in the competitive marketplace.
In a climate of budget constraints and cutbacks, the thirst for technology continues to swell, with businesses demanding increased capabilities and services. How are organizations steering through these conflicting pressures, and where are they uncovering efficiencies to strike the right balance?
To navigate these conflicting pressures and strike the right balance, organizations are adopting strategic approaches while focusing on reducing the total cost of ownership of technology.
One key strategy is prioritizing investments in technologies that align directly with business objectives, delivering tangible value and addressing specific pain points. By conducting thorough assessments and evaluations, organizations can identify areas where technology can drive code, process and operational efficiency, enhance customer experiences, and generate cost savings. This targeted approach ensures that technology investments are purposeful and contribute to the organization’s overall goals.
Additionally, some companies are leveraging cloud computing and software-as-a-service solutions to optimize their technology infrastructure. Cloud-based services offer scalability, flexibility and cost-efficiency, allowing organizations to reduce capital expenditure and ongoing maintenance costs.
By migrating to the cloud and adopting SaaS solutions, businesses can access the latest technologies and capabilities without significant upfront investments, thus reducing the total cost of ownership.
Process optimization and automation are further ways organizations are uncovering efficiencies. By streamlining workflows, eliminating manual tasks and implementing intelligent automation, businesses can enhance productivity, reduce errors and allocate resources to more strategic initiatives.
Technologies such as robotic process automation and AI enable companies to automate repetitive tasks, improve operational efficiency and lower costs.
Collaboration and strategic partnerships also play a vital role in overcoming budget constraints.
Organizations seek alliances with technology vendors, managed service providers and industry peers to leverage shared resources, expertise and cost-sharing models. Collaborative efforts enable access to specialized skills, innovative solutions and economies of scale, contributing to reduced costs and optimized technology operations.
What have been the most impactful efficiency gains within organizations you have worked with and how have these changes been received by both the technology teams and the wider business?
In the organizations we’ve worked with, the most impactful efficiency gains stem from optimizing technology resources and streamlining processes. Focusing on the top 1 percent of resource-intensive application and database code has led to a remarkable average resource reduction of around 50 percent in enterprise environments, significantly lowering total cost of ownership.
These changes have garnered positive responses from both technology teams and the business, manifesting in improved application performance and stability. Technology teams appreciate the increased performance and reduced complexity, while the wider business benefits from enhanced system responsiveness and scalability, elevating customer experiences and productivity.
Moreover, we’ve tackled technical debt and addressed inefficiencies, resulting in a substantial reduction in the total cost of ownership of in-house technology and SaaS services. This has freed up resources for innovation and growth initiatives, fostering a culture of continuous improvement throughout the organization.
Overall, the pursuit of efficiency has become a top priority for technology organizations, leading to resource optimization, lowered operational costs and increased competitiveness in the market. As a CEO, I firmly believe that optimizing efficiency is both a strategic imperative and a pathway to transformative success in today’s rapidly evolving business and technology landscape.
Looking forward, as technology and data demands continue to grow, where do you anticipate the next opportunities for efficiency and value creation might lie?
As we look ahead, the next opportunities for efficiency and value creation are likely to lie in further optimizing data management and processing capabilities. Embracing advanced analytics techniques, such as machine learning and AI, will enable us to uncover deeper insights from the vast amounts of data at our disposal. Additionally, leveraging cloud-native technologies and architectures will enhance scalability, flexibility and cost-efficiency.
Moreover, focusing on automation and intelligent systems will streamline operations and reduce manual efforts, freeing up valuable resources for more strategic endeavors. Data lifecycle management will play a pivotal role, allowing us to identify and prioritize high-value data while efficiently managing low-value or outdated information.
Collaboration and integration across diverse technology stacks and applications will foster seamless workflows and enable better data sharing, leading to enhanced collaboration and more informed decision-making. Lastly, addressing technical debt and legacy systems will be critical to modernize IT infrastructure and ensure a sustainable and agile technology environment.
By staying at the forefront of technological advancements, embracing innovation and fostering a culture of continuous improvement, we can seize the opportunities ahead and create value for our organizations and customers alike.
