Master the path to data-driven excellence in 4 steps

Massive data streams are pushing businesses to be more data-driven than ever before, but fewer than 30% of organizations can evaluate data fast enough to stay on top of their game, according to Gartner. Companies are overwhelmed with data. An astounding 2.5 quintillion bytes of data is projected to be generated every day in 2024 reports Big Data Analytics News. As companies embrace digitization, they need a plan for properly collecting, storing and learning from all that material. Data-driven organizations strategically harness the power of their data to generate actionable insights that inform business decisions. “An organization’s data modernization journey is often a vital part of a broader digital transformation,” Kforce Consulting Solutions Data Practice Leader Brad Boyd said. “Building a data-driven culture is not a one-time process, but rather a continuous evolution.” Companies that are successful at this often have a competitive edge in their industry because of their ability to deeply understand customer expectations and behavior, predict trends and quickly make well-informed decisions and adjustments.

These steps are fundamental for organizations beginning or reinitiating the path to data-driven excellence:

From strategy to implementation, we provide the knowledge and leadership our clients rely on to accelerate their business. Our proven team takes a unified approach to driving large-scale change and unlocking new opportunities for growth and success.

Custom solutions to achieve your goals

This Ruler is for the Space Between the Bottom of the Hero/Header Text and the Subheader Copy. Check Your Spacing for Consistency.

This Ruler is for the Space Between Text/Buttons/Callouts. Check Your Spacing for Consistency.

Unleash the power of your data: A journey of transformation

This Ruler is for the Space Between Modules/Macros/Sections. It Should Reach from the Bottom of the Previous Module/Macro to the Top of the Next Section.

Connect with me

Brad Boyd

MEET THE AUTHORS

PRACTICE LEADER Data & Analytics

Connect with me

David Nelson

PRINCIPAL CONSULTANT Data & Analytics

LET'S TALK CUSTOM SOLUTIONS

4 steps to data modernization success

“An organization’s data modernization journey is often a vital part of a broader digital transformation. Building a data-driven culture is not a one-time process, but rather a continuous evolution.”

Brad Boyd Data Practice Leader Kforce Consulting Solutions

1. Identify business objectives

The first step to being data-driven is identifying the specific goals and objectives your business wants to achieve with its data. This requires an understanding of your organization’s strategic and operational goals. Identifying the specific problems your business is facing will enable you to choose the right key performance indicators (KPIs) to measure and equip you to make informed decisions rooted in data. “Longer term, ensuring a strong connection between business objectives and data strategy benefits an organization’s communication and collaboration between departments, as everyone has access to and understands how to use the same information to achieve those common business objectives,” said Boyd. “Connecting business and data strategies simply leads to a more nimble, agile and responsive organization.”

2. Implement a single source of truth

Massive amounts of data are flooding businesses and overwhelming leaders as they spread across disconnected systems. A survey from Salesforce found that organizations use over 1,000 applications on average, but 70% of those apps remain disconnected from one another and the core business. This leads to an organization full of data silos, runaway costs, duplicative work, productivity bottlenecks and disconnected experiences. History has shown that silos emerge naturally where there is domain and data model complexity. “Organizations with large and diverse data ecosystems are shifting away from centralized data management towards managing data as a product,” said Kforce Data & Analytics Principal Consultant David Nelson. “Operational data assets are analyzed to identify usage trends and relationships, forming the basis of domains. These domains are then integrated with descriptors of business context to develop data products. Supported by federated governance, these data products are cataloged and offered for reuse based on the requirements of the business." According to McKinsey & Company, this approach towards domain data management can deliver new business use cases as much as 90% faster.

3. Present data for meaningful insights

The next step is to develop intuitive self-service platforms supported by purpose-built data products to empower data consumers with access to reliable and reusable data, enhancing decision-making capabilities. "Data consumers have evolved from traditional applications and reporting platforms," said Nelson. "Both discovery sandboxes and external data sharing have become common. Advanced analytics systems which generate new insights using machine learning and AI are receiving significant attention." Data is only valuable when leaders act on the insights provided. Data-driven organizations use business intelligence to make crucial corporate decisions. “The goal is to implement a structure where everyone in the organization is empowered to analyze data and apply it to their strategic goals,” Boyd said. “We want data-driven decision making to be a natural part of each team’s workflow.”

4. Foster a data-centric culture

Implementing the right tools and processes is one thing. Shaping culture is another. In a truly data-driven organization, each employee approaches their work with an analytical mindset. They lean on metrics and trends rather than opinion and anecdotes to make decisions. To achieve this, you must democratize data to ensure actionable insights are accessible to everyone. Every employee should have self-service access to the relevant data and metrics necessary to improve their decision-making process. Additionally, expand data literacy throughout your organization by training and upskilling your employees on data analytics skills needed in their roles.

Whitepaper: Preparing your organization for generative AI

Success story: AI chatbot empowers team with real-time sales insights

Kforce survey: Quality and security dominate data and analytics concerns

Success story: AI chatbot empowers team with real-time sales insights

Whitepaper: Preparing your organization for generative AI

Big Data Analytics

Salesforce

McKinsey & Company

SPACE IN BETWEEN BUTTONS

SPACE IN BETWEEN MODULES/ Macros/ Sections

SPACE IN BETWEEN HEADER AND SUBHEAD + Subhead & Body