This is a session recap of information presented by Bill Martin, Garr Williams & Greg Frasca during 3Cloud’s Envision Summit.

It is vital to align your data and analytics strategy with your business goals. This session provides a deep dive into the art of building and nurturing a data-driven culture to help businesses unleash the full potential of their data assets.

Data Assets Create Business Value

An effective data strategy is necessary to unlock the full benefits of your data assets.​ The business benefits of a robust and scalable D&A program are well documented. Measurable success is being achieved across all industries and all types of organizations.​

To stay ahead of your competition, you MUST move towards becoming a data driven intelligent enterprise. Business is driven by people and processes. Data is produced and consumed by business processes. Data is the lifeblood of your business.  A truly intelligent enterprise is dynamic in its ability to predict customer needs and reconfigure business processes to fulfill those needs.

Companies Face Multiple Data Challenges

Here are some of the challenges we encounter with our Data Blueprint clients

  • Same metric, different results – metrics calculated differently or different definitions among departments
  • Data Silos – data kept at department level for their specific use and not shared with the organization; sometimes in MS Excel or Access
  • Data Source Confusion – multiple versions of data found and confusion on which one to use for which purpose; also, old legacy data that is questionable
  • Poor Data Quality – data from source systems that is incomplete, inconsistent, or inaccurate
  • No Data Access – only IT has access to data causing a bottleneck for new reporting requests
  • No Trust in Data – business does not trust the data for a variety of reasons: IT does not understand what they need, poor definitions, bad data quality, etc.
  • No Accountability – no one identified to address source system data quality issues (data owner or data steward)
  • Shadow IT – departments stand-up own mini-D&A organization for their own purpose with no accountability for data inaccuracies or data misuse
  • Data Privacy – uncertain how to address new privacy regulations (CCPA, GDPR, HIPAA, PII, others)

Achieving ROI

While some organizations successfully leveraging their data, many do not.  Despite making investments in data and analytics, many organizations still struggle to get value from their data. In a study by Harvard Business Review only 20% of organizations are empowering their employees with the tools needed to make decisions from their data. Organizations know they need to change the way they use data, but what’s missing is an action plan that aligns the business objectives and data strategy. This is the difference between those who succeed and those who continue to struggle.

Planning and Strategy

Let’s define the basic steps of successful data strategy.

  1. Assess the current state of your people, processes, technology, data, and governance to understand the starting point for your analytics journey.
  2. Energize and align your organization with a unified vision for data and analytics to meet current and future business needs.
  3. Deliver a pragmatic and actionable strategic roadmap and modern data architecture recommendations to make the vision a reality.

Data Maturity Drives Business Value

An effective data strategy will drive data maturity and maturity equals business value. Business value equals organizational excitement, momentum and a willingness to continue investing in your D&A program.

Without strategy and execution against a well-defined plan, there is significant risk of sub optimal outcomes and business fatigue. A successful data maturity journey requires coordination of people, process, technology and data. 3Cloud’s approach to data strategy aligns these focus areas to specific high value business needs to ensure optimal outcomes and build momentum within any organization.

The Data Maturity Process

  1. Business Monitoring: Leverage data and analytics to monitor business processes. This consists of Data Warehousing and Business Intelligence reports and dashboards and identifies what has happened throughout the business.
  2. Business Insights: Uncover actionable customer, product, and operational insights and predict what will happen next. This primarily consists of Predictive Analytics and Data Mining
  3. Business Optimization: Automate the optimization of key business processes. Embed Prescriptive Analytics, such as recommendations engines, into business applications
  4. Business Data Monetization: Leverage customer, product and operational insights from Business Insights and Business Optimization phases to create new monetization opportunities.
  5. Business Metamorphosis: Enable a culture that encourages continuous exploration, creation, sharing, reuse, and refinement of an organization’s digital and human assets 3Cloud has helped many clients to successfully navigate their maturity journey.

What is a Data Strategy?

Data Strategy is Business Strategy. An intelligent enterprise is a successful enterprise and without a robust data strategy, ascension to becoming data driven is a path fraught with risk, uncertainty and wasted resources.

  • A data strategy is an organizational approach to manage, secure, and utilize data to achieve specific business goals and outcomes.
  • Data is treated as a corporate asset and extends into the people, processes, and technologies that are employed to leverage data for improved insights.
  • A well-executed data strategy can lead to greater operational efficiencies, improved customer understanding, enhanced innovation, and overall competitive advantage.

Successful data strategies are business-centered. A well-rounded data strategy begins with a business-centric focus and outlines the necessary steps to leveraging data through leadership, technology, governance, and training/upskilling.

Company Goals Are Enabled Via Data Strategy

At the center of everything is making sure that your data and analytics strategy is centered on rallying around the needs of the business. These may be annual or quarterly goals, they could be reactionary to sudden shifts in the market, they could be based on a merger or acquisition, or they could be based on a replacement of leadership within the organization. Whatever the reason, it’s important to continuously take inventory and adjust.

When setting goals, the leadership in your organization should take into consideration the measurement of the changes being implemented and the resulting outcomes. A sound data strategy has a seat at the table when creating these goals. If an organization is setting true, achievable goals, they should be able to measure these goals in a factual, pragmatic way.

The reality for many organizations is that IT and business goals are managed separately, or at least not aligned well enough to implement using an organization-wide approach. This practice must change to implement a successful data strategy.

Data Strategy Needs Strong Business Ownership

Every business needs a company-wide data plan. Unfortunately, there is still a widespread perception among business executives that data and analytics is purely an IT matter. A sense of ownership and the willingness to collaborate with other business units and IT is of the utmost importance in a strong D&A program. Effective data strategy does not use a set-it-and-forget-it approach. It is built on continuous collaboration, iteration and innovation, and those things are being guided by the needs of the business.

Effective Data and Analytics Require an Adaptable Architecture

3Cloud recommends a “Data Lake House architecture” to seamlessly combine the flexibility of a data lake with the structure of a data warehouse. The Data Lake House enables companies to store, analyze, and extract actionable insights from a diverse set of data sources, using low-cost and open storage formats.

Governance Increases the Business Value of Data

Data governance and oversight ensures data is used appropriately, protected from unauthorized access or misuse, and managed in a way that ensures its accuracy and integrity. A strong data leader and governance committee will possess the necessary skills and experience to collaborate with business executives, implement effective data governance policies and processes, and ensure that data is accurate, reliable, and consistent across the organization, leading to better decision-making, compliance, and efficiency.

We recommend that Data Governance is weaved into your data estate as necessary and should be run by someone with a strong background in the space. Additionally, the roles and responsibilities of those in a data governance practice such as a data steward or owner, should be communicated carefully, with change management in mind.

At the end of the day, it’s important for data governance to find harmony between control and flexibility.  When it does, and the proper people, process, and technology are put in place to support it, it will actually decrease the reactionary burdens on your business.

Data & Analytics Serve Enterprise and Departmental Needs

The classic IT approach to reporting is outdated for organizations responding to a constantly changing business environment. Companies want reliable enterprise level reporting with consistent KPIs to keep everyone aligned with organizational goals, AND the flexibility for individual departments to create their own reporting based on their unique tactical needs.

A hybrid reporting and analysis approach provides the organization with consistent enterprise reporting, while also enabling individual business units and departments to generate reporting based on their unique tactical needs. Data for both enterprise and departmental reporting is provisioned from a single D&A environment to ensure data quality and consistency.

New Data Skills Are Needed Companywide

Data literacy is essential in driving business value. Data Literacy is the ability to read, write, and communicate with data in context and is an underlying component of a successful data strategy. Your technical team needs the skills to support and enable advanced data technologies. AND your business team needs to understand and utilize data to generate actionable insights.

Data & Analytics Metrics

Data & Analytics program effectiveness can be measured using key performance indicators (KPIs). Metrics will depend upon the unique data challenges facing each organization. Examples can include:

  • Data Quality: measuring data consistency, completeness, and accuracy (reasonableness) during the data transformation process.
  • Data Definitions: measuring the increase over time of frequently used common data elements that have established business definitions.
  • Data Utilization: measuring frequency of use for data in a common data reporting repository; enterprise and departmental data usage.
  • User Satisfaction: measuring data user satisfaction over time to establish a trend; is data meeting business needs?

Getting Started

Successful data strategies begin with projects that will provide high business value and low implementation complexity.

Quick wins allow project teams to “fail-fast”, adapt quickly, and provide actionable business results for the organization. Quick wins also build support for the leadership and operational areas of the business that translate into sponsorship for future D&A projects.

Generative AI: The Next step in the D&A Journey

Generative AI absolutely needs to be a part of your data strategy. From a business perspective, generative AI is revolutionizing growth. But be mindful that standing up generative AI solutions is not an easy button. The ease of use of tools like ChatGPT can cause people to oversimplify generative AI. Proceed with caution. If there was any question of the value of data strategy, that question is being put to rest by the requirements of generative AI.

Generative AI requires high quality data to provide accurate results and insights. Organizations that focus on a robust Data Strategy that includes data quality, consistency, and accuracy will be better positioned to leverage generative AI as a competitive advantage.

3Cloud Data Blueprint Approach

A business-driven robust data strategy project addresses people, process, technology, and data to deliver a comprehensive organizational plan to unlock the power of data & analytics and drive organizational change and significant business value at scale.

3Cloud’s approach to developing a data strategy has a track record of success. From large enterprises to smaller mid-market organizations, we provide an effective and affordable method to build your plan and put you on the path to success. Contact us to learn more about Data Strategy today.