One of the most effective ways to advance enterprise digital transformation is to go to the lowest common denominator in the organization: data.
All of the keystrokes, entries, transactions, touchpoints, and conversations internally and externally by all entities that come into contact with your company result in data that’s recorded, stored, cleaned, managed, and distributed in the course of daily business.
So if data is the ubiquitous elephant in the room, why are corporate leaders, their teams, and even individual staff still wandering in darkness with data that can be incredibly useful and transformative to them? How can employees productively work toward common goals if data siloes disrupt workflows, impede digital progress, and generate unwarranted IT bloat?
Data democracy is foundational to speaking the same language. And it’s an accelerant to real transformation.
What Is Data Democracy?
Data democracy or democratization is the continuous objective of providing employees with access to relevant data that can enable better, data-informed decision-making and increase the organization’s collective comfort and confidence using data for various purposes.
By removing unnecessary technical barriers to data, organizations can elevate cross-functional collaboration, enhance customer and employee experience, encourage greater innovation, and synchronize workflows on common platforms without requiring IT expertise or hands-on intervention. Now, non-technical users can contribute more meaningfully and strategically to enterprise objectives.
Additionally, democratized data increases productivity and efficiency at the individual staff level, team or departmental level, and enterprise level as data flows more freely without silos. Helpdesk tickets, persistent chats, and unresponsive requests for platform permissions that often plague speed-to-decision can be overcome by improving employee data access that’s imperative to their roles and daily needs.
Data Transformation First, Enterprise Transformation Second
Data democracy isn’t out of reach, even if it may seem like an aspirational concept. In fact, there’s often consensus across departments that tangible action on transforming data and data processes should be taken.
For example, finance and IT leaders have bipartisan agreement that increased visibility through mutual knowledge-sharing and cross-functional alignment supports the digitization of end-to-end processes. Data, of course, is a key component to mobilizing toward this goal.
Additionally, visibility can incentivize teams to engage cross-functionally (45%) to produce stronger processes and synchronize cross-department operating models and rhythms (42%) – directional outcomes that data democracy can facilitate.
These are key findings from a Forrester Consulting survey of 300+ senior finance and IT leaders commissioned by CrossCountry Consulting.
See what 300+ Finance and IT executives say about the state of enterprise digital transformation.
New Forrester research commissioned by CrossCountry Consulting
To achieve this level of harmony, however, it’s critical that leaders prioritize a holistic data strategy, one that can underpin and inform future digital transformation efforts.
Data is the binding ingredient between cross-functional activities – if the data strategy isn’t consistent across the enterprise, organizations often end up deploying more functional point solutions that have limited utility to anyone outside a siloed business unit. Plus, disparate organizational data can quickly lead to data mismanagement, competing governance structures, and general underutilization.
To generate more value and alignment from data, organizations must:
- Define and document clear business objectives: What are the specific business outcomes to achieve with data? What’s motivating transformation? These questions must be explicitly and clearly answered to ensure the data strategy is fully aligned to the corporate strategy.
- Identify data sources and needs: What data does the organization currently have, where is it stored, how is it managed, who owns it, and how is it used? These baselines help to inventory the current state and spotlight gaps, risks, and opportunities.
- Implement a data governance framework: Establishing appropriate governance over data management practices ensures data is measurable, manageable, auditable, and useful to relevant internal and external stakeholders. The data governance framework should include roles and responsibilities, controls, and processes for understanding, storing, sharing, and acting on data.
- Invest in modern data technologies: Data cloud and automation tools like Snowflake, Alteryx, and Fivetran can store, migrate, and action operational data from across disparate sources and systems for strategic analytics, business intelligence (BI), machine learning (ML), and artificial intelligence (AI) capabilities. Additionally, 78% of finance and IT leaders indicate they’ve implemented, plan to implement, or plan to expand cloud data warehousing for the express purpose of facilitating more effective digital transformation. Leveraging best-in-class data technology of these kinds is imperative to embedding data democracy and taking the next step toward enterprise-wide digital transformation.
- Build a data-driven culture: By democratizing data and establishing data literacy across the business, each function shares a common language and vision concerning the impacts of the enterprise data strategy. As teams align on data use cases, they are more motivated to maximize the value of data within their day-to-day and are more agile to the new technologies and processes that are necessary for concurrent and continuous transformation over time.
- Promote data-driven hiring: Applying modern data management and innovation practices to current staff and processes is important to leveling-up in the near term, but organizations must also embed a data-driven mindset into their hiring strategies. With an evolving job and skills market, organizations can tap into candidates who already have proficient or advanced data skills they can bring into the firm on day one. In some cases, the nature of job roles might shift: Rather than seeking “traditional” applicants for accounting roles, for instance, organizations can re-align these job responsibilities to be more technology-enabled than in the past. In this way, each external hire helps move the needle on data transformation and expands upon the existing data-driven culture.
While data transformation may not be the most conventional starting point for broader transformation (in many cases multiple transformations occur simultaneously), it can enable more informed, cleaner decision-making now and in the future.
From Visibility to Value: Connecting the Dots
Embracing data democracy enables teams across the organization to share accessible information and technology platforms they may not otherwise leverage. Empowered with this newfound touchpoint and level of connectivity, it becomes easier for staff from different functions to work together on end-to-end processes (e.g., IT collaborating with accounting on close management processes and software, finance collaborating with risk management on automation, or HR and marketing collaborating on branding campaigns to recruit talent).
Tech-driven platforms that deliver scalability and speed are the top-cited mechanisms for finance and IT in particular to align, according to the study. Once aligned, leaders believe AI/BI-based decision support will be foundational to their organization’s digital evolution.
As mentioned, digital evolution is not possible without a holistic data strategy. With visibility into data, staff can tap into and generate new value streams.
These value streams are evident in:
- Improved decision-making: When teams have clear visibility into their data, they can make better decisions about everything from product development to marketing to customer service. They can also identify areas of improvement and deliver insights up the chain of command more quickly.
- Smarter processes: When leveraging data analytics and business intelligence platforms, staff can uncover process inefficiencies, cost overruns, and labor savings. Staff can also clarify which stakeholders are responsible for certain handoffs and workflows that stretch across teams to ensure common transformation challenges and obstacles are understood and overcome efficiently.
- New products and services: Data can help organizations to understand their customers’ needs and wants, and to develop new products and services that meet those needs.
- Improved data quality and security: Data lineage can help organizations identify and correct errors in data, mitigate security risks, and maintain auditability.
- Improved data compliance and governance: Enforceable governance policies and procedures enable organizations to comply with regulations (e.g., data privacy) and maintain a strategic, cohesive approach to data.
- Enhanced digital transformation outcomes: Security, innovation, and agility are the most sought-after outcomes of digital transformation, according to the study. Data visibility and data quality are imperative to accurately measuring these outcomes, reporting progress, and considering transformation “complete” or “successful.”
Driving data transformation, beginning with data democratization, is central to long-term enterprise agility and competitive differentiation. There’s no time to waste.
To explore more expert insights on the state of today’s enterprise digital transformation, download the full study. And to expedite your next transformation, contact CrossCountry Consulting.