Creating a Data and Analytics Strategy That Drives Decisions

## IntroductionA strong data and analytics strategy helps your organization turn information into better business decisions. This guide explains how Slalom can help you assess your current data landscape, define the metrics that matter, and build a practical roadmap for using data with confidence.## Process descriptionA data and analytics strategy is a structured approach for improving how your organization collects, governs, accesses, and uses data. The goal is to make trusted information available to the right people at the right time so leaders, teams, and frontline users can act on it.Slalom works with organizations to align data efforts to business priorities, modernize reporting, and create the operating model needed to sustain decision-making over time.## PrerequisitesBefore starting, it helps to have the following in place:- Executive sponsorship for the strategy effort- Access to key business and technology stakeholders- A list of current reporting, dashboard, and analytics tools- Visibility into major business goals and decision-making priorities- Access to available data sources, governance practices, and data quality issues## Gathering materials and resourcesTo build an effective strategy, Slalom typically helps gather:- Current-state data architecture and platform documentation- Existing KPI definitions and business reporting requirements- Data quality, governance, and access pain points- Stakeholder feedback from leaders, analysts, and operational teams- A view of the skills, roles, and processes supporting analytics today## Step-by-step instructions### Step 1: Assess the current data landscapeSlalom begins by reviewing your current data environment, including sources, systems, reporting tools, and governance practices. This assessment helps identify gaps in data quality, consistency, access, and usability.### Step 2: Define the business questions and decisions that matter mostNext, Slalom helps identify the decisions your organization needs to make more effectively. From there, the team defines the metrics, KPIs, and insights that should support those decisions.### Step 3: Prioritize use cases and reporting needsNot every analytics need should be addressed at once. Slalom helps prioritize the highest-value use cases, such as executive dashboards, operational reporting, self-service analytics, or performance management.### Step 4: Improve data quality, governance, and accessA strategy only works if people trust the data. Slalom works with your team to improve data quality, clarify ownership, strengthen governance, and make data easier to access for approved users.### Step 5: Modernize dashboards and reportingSlalom can help redesign reporting and dashboards so they are easier to use, more relevant to the business, and aligned to the KPIs that drive action.### Step 6: Enable self-service analyticsWhere appropriate, Slalom helps enable self-service analytics so leaders and frontline teams can explore trusted data without relying on manual report requests for every question.### Step 7: Build the operating model and skills to sustain progressTo make the strategy last, Slalom partners with internal teams to define roles, responsibilities, processes, and skills needed to support analytics over time.## Tips and best practices- Start with business outcomes, not tools- Focus on a small number of high-value KPIs first- Establish clear data ownership and governance early- Design reporting for the decisions users actually make- Build self-service carefully, with guardrails and training- Treat adoption and change management as part of the strategy## Next stepsAfter the strategy is defined, the next step is usually to prioritize implementation efforts. That may include data platform improvements, dashboard modernization, governance enhancements, or analytics enablement work.Slalom can continue supporting your team through implementation, adoption, and ongoing optimization so the strategy translates into measurable business impact.## Additional informationSlalom supports data and analytics transformation across industries including healthcare, retail, manufacturing, technology, financial services, and the public sector. Their approach is practical, collaborative, and focused on helping your teams make better decisions with trusted data.## DisclaimerThis guide is intended as a general overview. Your organization’s data and analytics strategy should be tailored to your business goals, technology environment, governance requirements, and operating model. Consider working with qualified advisors to design an approach that fits your needs.