Establish Your

Analytics Operating Model.

Your Situation and Challenges

Organizations are struggling to understand what is required to go through the analytics developer lifecycle and generate reusable insights.

Discover what it takes to become a citizen analytics developer. Identify the proper way to enable self-serve analytics.

Self-serve BI/analytics is misunderstood by and confusing for the business in terms of IT’s and the business’ roles and responsibilities. End users’ dissatisfaction is often due to a lack of access to the data and a single source of truth.

Self-serve analytics does not mean simply transitioning IT-driven analytics to the business. Since lines between business and technology are blurring, SDLC and development are no longer limited to the technology part of the organization.

The business’ analytics need to go beyond one-time, self-service data analytics. Move toward reusable insights that the business can operationalize and act on by adopting a proper data analytics operating model.

The goal should be to accelerate the speed of analytics and data-driven decision making.

  • Adopt design thinking and minimum viable analytics products or services.

  • Align your analytics leadership to data governance.

  • Map your analytics capabilities to a hub-and-spoke model.

  • Draft and organization structure and RACI for analytics.

  • Refine your engagement model.

  • Formalize a communications plan.

Situation

Challenges

Insight

Critical Elements

Organizations must think about value-added data products and services at all levels. But most organizations are stuck in traditional thinking of self-service analytics.

An organization’s structure, process, people, and technology functionality are the main components of the analytics operating model. These four components are aspects of analytics that can be changed in the near term to improve performance

Three Options To Get Our Help With Your Analytics Operating Model

  • You are responsible to define your Analytics Operating Model. We provide the structure, framework, templates, and a set of calls to accompany and advise you.

    Each call will focus on explaining the material and helping you to plan your Analytics Operating Model, interpret and analyze the results of each step, and set the direction for your next activity.

  • Incept is responsible to lead the delivery of your Analytics Operating Model.

    A consulting team will be assigned to your Analytics Operating Model project. We will lead and together with you, define your Analytics Operating Model.

  • Most organizations already have an operating model, but they try to improve it when they can. If this is your case, we can easily turn this service into an assessment. You will obtain a report covering all the items in the below section.

Strategy

Operating Model

Execution

Where should we play?

How can we win?

Take into account culture and values.

What is the problem?

What is happening in the business now?

What are the potential opportunities?

Where and how is the most critical work done?

How do we compete?

How do we add value?

How do we interact?

How do we position data products/services to compete?

How do we organize staff for analytics development and delivery?

How do we interact with the  organization for decision making?

How do we ensure awareness of and adherence to analytics standards?

How do we implement a solution effectively?

Detailed organizational design

Detailed structure and specific decision-making roles

Processes, information flows, technology, and tools

Detailed metrics and a feedback loop

Talent system and incentives

Cultural reinforcement

Deliverables

  • This step is to understand your organization's data analytics goals and objectives. During business workshops and interviews with key data stakeholders, we aim to capture your analytics goals and objectives and map them to your data stakeholders. We capture the following information below:

    - Data warehouse modernization ideas harvested from these interviews and workshops.

    - The session each idea was obtained from (so you know who to go back to for further details, if necessary).

    - The strategic direction of the idea (e.g. customer intimacy, product innovation, operational excellence).

  • Based on pros and cons, we help you through the choices of Centralized, Hub-and-Spoke/Business-Driven, and Hybrid/Managed Services Analytics

  • Most reporting and analytics responsibilities fall into a grey area in many organizations, including building analytics, establishing capabilities, and creating a reusable framework. We ensure that we not only eliminate those grey areas, but that we clarify what needs to happen to get there.

  • The engagement model is the mechanism used to coordinate the communication among, and contributions from, everyone involved in the organization’s reporting and analytics practice. Reporting and analytics is an enterprise-wide practice that aims for continuous process improvement and involves many stakeholder groups at different levels across the organization’s hierarchy.

Clarity is important. Having a firm grasp on what’s expected when you engage us, including objectives and deadlines, is crucial to your success. We like to make things clear so you know what you’re getting.

Contact us.

Analytics is a journey, not a destination. This journey can eventually result in some level of sophisticated AI/machine learning in your organization. Every organization needs to mobilize its resources and enhance its analytics capabilities to quickly and incrementally add value to data products and services. Let Incept help you mobilize your resources in this way.