How to Build an Enterprise Data Strategy Framework – Getting Started
Data is central to any business, and the ability to strategically manage it is growing exponentially. As companies lean in on digital transformation efforts, their data strategy will be a true marker of their ability to compete and future-proof their business. According to Harvard Business Review, “cross-industry studies show that on average just 26.5% of organizations report having established a data-driven organization (2022).” Although the ability to effectively manage an abundance of data is integral to a business’s success, many organizations continue to operate in legacy systems with little-to-no data architecture, unable to integrate data across sources, relying on disparate data sets, manual processes and antiquated spreadsheets. This significantly limits their ability to create operational efficiencies and cost savings, explore new product/service revenue opportunities and create a better customer experience.
In this article, we will explore the framework of building an enterprise data strategy that can be applied across industries.
Define Business Objectives
Building a data plan with people, processes and technology interwoven into the framework is the foundation of a strong data strategy. An effective strategy centers around the business problem an organization is attempting to solve and begins with clearly defining business objectives. These objectives and use cases should align with the organization’s strategic goals and be clearly measurable. Most importantly, executives and business stakeholders must be in alignment with the defined objectives and understand not only the unified vision, but the execution steps needed to build a data-driven culture.
Current vs Future State
Meeting with executives and business stakeholders across departments and within every line of business is required to understand existing sources of data and how it aligns with business and strategic objectives. Mapping out present workflow and ideal future state will assist in gaining a deeper understanding in the data, how it flows, and the leveraged technology and systems.
Take note of the current infrastructure and technologies established to determine if these systems have the power to deliver on the defined strategy, both in the immediate and sustainable future. Business Intelligence and Analytics Platforms and advanced technologies, such as Cloud Platforms, Artificial Intelligence (AI) and Internet of Things (IoT), as well as predictive analytics, should be considered and integrated as needed to deliver a secure and modernized data strategy.
Understanding the data topology will identify obstacles and narrow in on areas where integrations may need to be refined. A data architecture and data management framework should be defined for how data will be created, stored, processed and transported. Again, this is where existing systems and technologies should be evaluated to determine if the present ecosystem can deliver on strategy or whether new and/or additional technologies should be considered.
Further considerations should be made to determine if an organization can leverage its data for productization and monetization efforts. There are multiple opportunities to monetize data by adding new services to existing offerings such as data and/or insights as a service or product, or creating a new business model More than likely, when an organization begins strategically analyzing their data, they start to realize that data is one of their most valuable and fluid assets.
Barriers to Change
Proactively identifying barriers prior to a transformation effort will streamline execution efforts and minimize disruption. Sizeable barriers, such as organizational data silos and data quality, can negatively impact data integration, management and workflow. In fact, research suggests that 82% of enterprises are hindered by data silos (IBM Garage, 2020). Building a self-service data environment where data is accessible to employees in a governed and centralized platform will further advance data-driven initiatives.
Data literacy must also be thoroughly evaluated within the existing workforce and the individuals implementing the data strategy. With consistent cadence of new and advanced technologies emerging, upskilling in data or hiring data-literate employees will place an organization at a significant advantage. Notably, Forrester’s research reports that 70% of employees are expected to work heavily with data by 2025 — up from just 40% in 2018 (U.S. Bureau of Labor Statistics, 2022). For organizations that invest in data literacy upskilling and training, benefits may include enhanced productivity, improved employee and client experience, and increased innovations.
Earlier we mentioned that people, process and technology are fundamental components of data strategy. While process and technology are equally vital, people are at the core of any significant organizational culture change and can either drive or hinder success. In a 2022 Data Leadership and AI Executive Survey, respondents report that 91.9% of executives cite cultural obstacles as the greatest barrier to becoming data driven (Business Wire). Ensuring that employees can access data in a self-service environment and turn data into actionable insights is a key differentiator when executing a successful change initiative.
Data Governance and Controls
An organization’s data governance plan will define data quality, privacy, security and management, and should align with the established data strategy and business objectives. Short-term tactical goals and long-term strategic goals should apply with an external consideration toward compliance and regulation requirements. A governance plan should document the organization’s data policies, and defining roles and responsibilities for those involved, with governance including who is responsible for collecting, storing and using the data, including a cloud platform to ensure optimal protection. The governance plan should be comprehensive and multilingual to each role to minimize delayed onboarding, assist with naysayers and evolve alongside organizational growth.
Communicating, Measuring and Revisiting Data Strategy
A comprehensive strategy defines the technology, processes, people and controls required to manage an organization’s data. Mapping out the data strategy and framework, and establishing effective communication channels from the executive team to key stakeholders to individual data-decision makers will be key to strategy adoption. Like the governance plan, the strategy should also be comprehensive and multilingual to each role to minimize delayed onboarding, assist with naysayers and evolve as the organization grows.
Key metrics should be established at the start of strategy implementation to measure progress. Quick wins should be shared organization-wide to amplify momentum and share business value. Likewise, metrics should be reviewed regularly with executives and business stakeholders to determine success and reevaluate priorities. It is important to keep in mind that a data strategy is a fluid approach and should be reviewed routinely to evolve and scale as the organization grows. Keep things simple, start small and build upon successes in defining and executing a data strategy.
About Cherry Bekaert Digital Advisory
Cherry Bekaert’s Digital Advisory team is comprised of strategists who have broad industry experience and keen business acumen. Utilizing an agile and flexible approach, we help examine what you want to achieve with a focus on people, process, technology and culture. We are here to help organizations manage risks, enable growth and support sustainable operations. Leveraging our strategic process, we help digitally enabled organizations – especially middle-market companies – do more with less. Cherry Bekaert stays on top of the latest technology trends, but we know that technology is not a one-size-fits-all solution. Cherry Bekaert is here to guide you on what technology makes sense to adopt as it pertains to delivering the highest value to your organization.
Data-driven companies outperform competitors by providing their workforce with data needed in real time to make smarter decisions. With a solid data strategy, organizations can build a healthy data culture that empowers people to make better decisions, drive efficiencies and fuel innovation that is necessary for businesses to remain competitive and agile.