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Designing to Serve: How to Make Your Insights Organization Work for Your Business

Are Your Data Insights Doing the Best Job for the Business?

Organizations today have an abundance of data at their fingertips, but it isn’t the “treasure trove” we often call it if insights are not delivering on the needs of the business. Many businesses have done the work of establishing an insights function—whether you call it an analytics center of excellence, a data science community of practice or an advanced analytics team. However, few have developed a true service model that ensures the business (e.g., marketing, operations, product development teams) is accessing insights critical to their work.

Technology and data are often the focus when these insights organizations are created. But the real value is in providing the service of intelligence. This means turning data into actionable and meaningful insights that drive value. This requires shifting your insights organization into a service organization centered on the needs of your internal business unit customers.

When this is done right, it is truly transformational.

Author

Daniel Liebermann

John Isenhower

Stephen Picard

Unlocking Value Through Tech and Data

Start with a fresh perspective

Insights organizations prove their value by leading the internal business units they serve to greater understanding and greater action. For this reason – building an insights organization starts with a clear internal customer value proposition and service model.

While there are varying levels of maturity across insights organizations, ranging from early stages of formation to being operational for years—all stand to benefit from these fundamental tenets when building a service model:

Put your internal customers first. Look at the structure, data, technology and other insights capabilities through the lens of your internal customers and how these elements can maximize value for them. Data and technology are necessary enablers, but they should not lead the design.
Know what you’re trying to solve. Understand the business problems your internal business unit customers are facing, as well as the frequency, fidelity, speed and process against which decisions are made.
Collect and build to purpose. Before collecting ‘all’ the data or starting to pursue time-consuming and expensive modeling and tool builds, let the needs of your internal customer drive your actions. Prioritize your customers’ needs and prioritize insights capability development accordingly.

A large healthcare network built a centralized insights portal to connect their network of doctors and hospitals with their analytics and insights talent.

This portal allowed their insights organization to collect and triage requests from across the enterprise. The portal also offered self-service solutions such as code sharing and a searchable insights repository.

These guiding principles are applicable across industries. For instance, a US government agency developed an insights service organization that converted the agency’s log data into business analysis and insights. The agency built and stood-up a service model to manage its internal customers and take insight requests. This model maximized the value of raw data by supporting decisions and building business relationships across the agency.

Structure with intention

So, we know what the service model needs to do, but how does an organization build it? An effective insights organization is structured around five dimensions and the most often overlooked is designing for internal customers. Again, for a more mature insights function, some of these factors may be in place, but it will be important to reassess them to make sure they are working cohesively.

And each pillar must answer specific questions to provide value to internal customers

1

Organization & Operations

The first step is establishing the service model and building the capabilities to enable it. The business will need executive buy-in and funding, and it should also begin by assessing the current model. Customer insight needs should guide decisions, so look at what those needs are, what the value proposition should be to deliver on those needs, and what will be the frequency of insights delivered and decision process. From there, the business can develop a fit-for purpose organizational structure, roles and responsibilities, competencies and key metrics.
2

Technology

Technology is the underpinning of the insights organization, and it must be efficient, flexible, scalable and secure. The business should look at what tools it needs to analyze data to generate and store data insights and share them with customers. This may include a suite of business analytics tools connected across data sources and can be used for scheduled, ad hoc or self-service analysis. Personalized dashboards with business rules and security built in will minimize manual processing.
3

Data

Data collection should be informed by the needs of internal customers to maximize the value of data collected, minimize cost, and increase the speed at which insights are created. The insights organization may start with a set of existing data and look to understand how it could be applicable for internal customers, or it may chose to collect data to fulfill specific business needs. In either case – insights organization governs, stores, transforms, and syndicates data with purpose.
4

Quality

Quality should permeate the insights organization. After all, it is difficult to recover from reporting the wrong numbers or generating a poor insight due to a quality issue. Doing so ultimately impacts how much the insights organization is trusted within the enterprise. To ensure this, evaluate the current process of requesting, creating and delivering insights and examine the controls that are in place to generate the highest quality insights for customers. Create a measurement framework and KPIs that measure the impact, output and quality of insights.