Put simply, data should solve business problems, not data problems.
Forrester reports that “data-driven companies grow on average more than 30% annually. But despite universal agreement that data has the power to improve decision-making across all parts of an organization, many companies are still struggling to make that a reality and reap the benefits.” Further, according to Gartner, “through 2022, only 20% of analytic insights will deliver business outcomes.”
Data driven decision-making is the backbone of modern business, with companies investing billions in technology to collect customer and operational data to improve insights and offerings. But simply collecting mass quantities of data doesn’t do the trick as we’ve seen example after example of missing the mark due to having the wrong talent, problem or even data itself. Many companies look to data to solve problems without ever having fully defined the problems themselves. Skipping this critical step leaves an organization with data it cannot effectively utilize.
So how does an organization achieve ROI on its data investment, especially in the face of ever-changing technology?
At G2O, we believe investing in a Data Strategy to guide your decision-making process is the strongest approach to ensuring success. Rather than collecting more data, the answer is in planning out the use cases that drive your business and building your data architecture around that framework.
What is a Data Strategy?
By starting with your business needs and applying data that helps solve these needs, you create a roadmap for investment in the data that will create real value for your organization. A Data Strategy Roadmap is what sets truly data-driven companies apart from those who are simply gathering inputs.
The strategy framework allows your company to answer complex business problems and achieve organizational goals, whether defensive or offensive in nature.
Defensive Data Strategy
- Approach focused on operational efficiencies and cost reduction.
- Typically, an IT function, how data can help streamline IT operations, system performance or reduce costs.
Offensive Data Strategy
- Approach focused on driving revenue, profitability and better customer engagement.
- Driven by Sales & Marketing or Product teams focused on driving incremental business.
In either approach, investing in a Data Strategy to build your modern data platform sets your business up to benefit from advantages including scalability, security and savings. Looking at the key elements of building your Data Strategy Roadmap, we’ll see each of these come to life in multiple ways.
6 Elements of Building Your Data Strategy Roadmap
To do more with your data, and have your data do more for you, creating a Data Strategy Roadmap involves a variety of elements and input from different areas of business operations. Our proven Data Strategy Assessment process helps companies create the data foundation they need to grow and reach their goals.
Follow these six steps to build a successful Data Strategy Roadmap:
1. Determine Business Priorities
Data goals MUST align to business goals. For your Data Strategy to produce ROI, you must know what problems your data needs to solve. Period.
Start by asking “Why” are you revamping and updating your data and “What” are you trying to achieve? And don’t just ask your department, conduct stakeholder interviews across your organization to understand what each department needs and levels of priority for each need. Tech may want to improve the stability of your operating environment so that the environment can scale to demands anticipated in the next 18 months while Marketing needs a single view of the customer to optimize the marketing mix in an effort to reduce acquisition costs. Ladder these department specific initiatives up to overall business drivers and objectives to weigh the operational investment of each and prioritize.
2. Source and Assess Data
With your business goals and priorities in hand, next we look to existing resources – what data do you already have that can address those problems? Is it the right data? Are there any problems with the data? Identify gaps in owned data to determine needs for 3rd party data, with a thorough understanding of what exactly you need external data to provide.
3. Establish Governance & Security Framework
Rather than an afterthought, data maintenance and governance should be an important part of the design process, ready to be deployed as soon as you start building to keep your data clean. Establishing ownership, ensuring knowledge share and information quality and managing accessibility and security all combine to improve the organizational business value of the data.
For Data Security, a four-step process of cataloging data, identifying users, designing roles and implementing privileges is recommended and monitored by the creation of dashboards to audit compliance. Data and privacy go hand in hand, keeping the challenge of managing rights and accessibility always at the forefront.
4. Establish Future-State Data Architecture
With data security measures in place, the next step is to define the technological needs by assessing the current data environment and architecture to confirm you have the right database and tools to create your data environment. In mapping out a data architecture, also create a reference architecture gap assessment with recommendations on how to close those gaps.
5. Activate Data into Insights
Analytics is the differentiator that turns your data investment into an asset. Culturally, this awakens a shift in mindset, from focusing on the data itself to the action, rooted in the business problem. The key in this step is to match how the decision-makers need to consume the data and then map out the analytics layer to meet their needs established in step one – whether it be self-service, dashboards, models and/or AI/ML.
6. Create a Final Data Strategy Roadmap
Taking all of the above elements into consideration, you can create a final roadmap setup for both initial execution as well as a foundation to guide years into the business’ future. At G2O, we employ a staged approach, coined “Crawl, Walk, Run.” Rather than retreat off in a silo to “build the thing” only to come back and find that the business has progressed in the time taken and morphed in many ways due to both internal and external factors, this tactic allows us to make a more immediate impact, establishing early guardrails, developing priority elements and laying the groundwork for expansions, automations and advancements in continued alignment with the business evolution.
From the initial timeframe (as few as 6 weeks) to the core execution (multiple months) and continued on down the road, the Data Strategy and complementary Roadmap align the business objectives, stakeholder buy-in and financial resources required to bring your data-driven organization from simply amassing information to effectively developing business moving insights.
Build Your Data Strategy Roadmap with a G2O Data Strategy Assessment
A solid assessment and strategy ensures your resources are appropriately dedicated and that your data investment returns real ROI. When you partner with G2O on a Data Strategy Assessment, we can both help you build your Data Strategy Roadmap as well as continue to work together towards its execution.
From data source identification/collection to prioritized use cases and a tailored architecture with conceptual infrastructure model, we walk side by side with your team from initial recommendation through the stages of tactical implementation.
Connect today with one of our Data Experts to learn more about how a Data Strategy Assessment can transform your business and produce true ROI.