Analytics wherever you are: Responding to COVID-19 with trusted self-service enterprise analytics capabilities

Responding to COVID-19 with trusted self-service enterprise analytics capabilities

COVID-19 has changed the way we work. But new work-from-home models put pressure on organizations in terms of infrastructure availability, computer power, and governance. Companies across industries are facing upheaval in terms of their analytics capabilities. They need a stable analytics foundation they can trust: one that balances the needs of individual employees working from anywhere with the needs of the organization.

In our recent webinar, Howard Dresner, Chief Research Officer of Dresner Advisory Services, shared his group’s 2020 survey findings of the importance of analytics as companies face the business impact of the COVID-19 crisis. The results suggest companies are prioritizing analytics more than ever, even as other business initiatives fall to the wayside in response to growing uncertainty and business loss.

The results show the impact of COVID-19 has been a system shock to companies’ business intelligence competencies. The crisis has fundamentally changed their approach. This article examines Dresner Advisory Services’ key findings and explores how companies can facilitate the growing need across industries for governed, “analytics wherever you are” capabilities.

Analytics investments remain strong despite other declines

In March 2020, 71% of companies claimed their budgets and projects were impacted by COVID-19—a figure that increased each subsequent week, reaching 84% by May 2020. Almost all companies were impacted, no matter their size or industry. But outliers in the results tell a broader story about analytics preparedness.

Healthcare and higher education, for example, were among the highest-impacted industries in the study. Both are regulated and complex industries, and both are less mature in their ability to leverage data and analytics compared to other industries. Broadly speaking, they have not invested in analytics and business intelligence like other industries, and many have been caught off guard.

All industries have been significantly impacted for similar reasons—they are unable to leverage data successfully given their lack of progress on analytics and the unprecedented nature of the current climate. In fact, 67% of companies have sustained some loss of revenue or have lost customers because of the pandemic.

But even as the number of organizations increasing their analytics spend dropped between March and February, 40% continue to increase their budgets for business intelligence and analytics. The number of companies who will maintain their current investments has also increased to nearly 47%, indicating that companies are still prioritizing analytics, even as they pull investments in other critical business areas.

Four approaches to analytics to boost opportunities in a crisis

Even amidst the crisis, companies see business opportunities. They must shift their business practices, however, to respond to the changing climate and maintain their teams’ capabilities to take on new challenges. The last 30 days of survey results indicate companies are doing just that.

For analytics, that means boosting their capabilities in four critical areas: self-servicecollaborationgovernance, and data storytelling. Indeed, access to analytics has become critical as employees transition to partial or universal remote work—perhaps even after the pandemic subsides.

The new environment means employees are required to access data regardless of a) their physical location and b) the underlying data formats that are stored. Employees must be able to access these capabilities wherever they are, and through whatever device they choose to use. They must be able to create content and access analytics in a governed but democratized way. As we will find, Pyramid Analytics has engineered a next-generation analytics platform specifically designed to accomplish these goals.

1. Growing interest in self-service capabilities built on trust

The results from Dresner Advisory Services tell us that self-service is becoming increasingly important in terms of making analytics pervasive—especially at scale for remote employees. Teams must continue making decisions about the business, even as their traditionally in-house call centers and support staff have become dispersed.

Democratizing analytics is among Pyramid Analytics’ foundational pillars, where technology aligns with successful self-service models directly. Pyramid Analytics supports any ordinary business user’s ability to conduct sophisticated analytics and leverage the results with a simple user interface and approach.

Pyramid self-service approach doesn’t mean analytics in isolation; it means analytics where users are free to explore data, while remaining connected to a network of other self-service users. Ultimately, it’s built on foundation of trust: users can flourish when they’re empowered to use data in a shared analytics environment.

As we will find, in collaborative environments that support data storytelling, self-service capabilities become a gateway to greater democratization of analytics access, wherever employees happen to sit.

This has in part become a technology problem. With an ever-faster migration to cloud-based computing, processing and storage resources have become effectively limitless. However, to harness this power in remote work scenarios, infrastructures must support “In-Place Analytics.” In-Place Analytics lets users perform analytic calculations—from basic to advanced—via a direct query into the underlying data storage engine without ingesting the data into a proprietary analytic database. This approach maximizes query performance, and emphasizes self-service capabilities so users don’t have to make unnecessary sacrifices in their day-to-day analytics endeavors.

We especially see the advantages of these types of self-service models in the pharmaceutical industry, where data access must be both highly accessible but also highly secure as employees access analytics from home. In the wake of COVID-19, employees can analyze millions of rows of data and analytics capabilities that reside on-premises as employees leverage insights from dispersed locations.

2. Collaborative tools that reside in analytics environments

For years, Dresner Advisory Services has tracked how companies share and derive insights from data. In recent data collected from February to April, Dresners’ data shows collaborative business intelligence capabilities have become increasingly important to organizations. Although interest in centralized collaborative tools has been growing for years, collaborative features built directly into business intelligence tools took a particularly substantial boost during this period compared to past results.

Business leaders want their employees to be able to share and annotate items in their analytics platforms, while keeping track of changes through unique collaborative features in their analytics software. As an example, Pyramid Analytics allows employees to build and share analytics models, data visualizations, dashboards, and more using an intuitive, codeless approach that can be managed wholly within the platform itself, rather than relying on separate applications that complicate security and governance and introduce integration challenges.

Not only can employees access content at very low levels of granularity as well—allowing them to share not just analytics visualizations and data, but business logic across multiple users—they can engage in real-time instant messaging conversations around the analytics they create, all within the platform.

These functions enable companies to maintain a central repository of data assets, even when employees access analytics remotely. Centralizing data functions reinforces employees’ trust in the data they access and the insights they share as well.

3. Maintain governance in democratized analytics environments

Dresner Advisory Services’ data suggests controlling and managing content creation and sharing has risen to well above average levels in terms of companies’ interest. Although this has been a consistent pattern over time, this interest increased considerably between February and March 2020, likely driven by current events. But companies must maintain a measure of governance in terms of how employees access and interact with data models and reports, especially within companies whose employees have become entirely remote.

Pyramid Analytics allows stakeholders to secure access by role, establishing permissions based on their data needs. The self-service environment itself can also be configured based on analytic skill. For example, platform administrators can assign full controls to seasoned analytic professionals, and simultaneously reduce advanced functionality for those with less sophisticated analytics needs. In this way, companies can strike the right balance between facilitating collaboration and maintaining governance and security of data and analytics content—not to mention accelerate engagement and user adoption.

4. Formalizing data storytelling as part of an analytics platform

Data storytelling—the process of using analysis and visualizations to tell a story with data in a compelling, actionable way—is both a skillset and an analytics capability that has been growing in importance for years. It has received heightened attention from users and respondents to Dresner Advisory Services’ surveys.

While widely adopted, data storytelling is rarely successfully and accurately executed. Mature organizations use data to drive storytelling, which in turn drives faster, defensible decisions. To rise to new levels of analytics maturity, companies must graduate from using desktop-only tools (and Excel, Word, and PowerPoint!) and begin to use their business intelligence platforms for data storytelling instead. That means accessing live data, shaping the story, and creating annotations in a single environment. Pyramid Analytics supports employees’ abilities to accomplish this, even as they interact with other features within the business intelligence environment.

Reliable business intelligence, no matter the business climate

The COVID-19 pandemic has impacted everyone. Like our friends, family members, and colleagues, company leaders across industries were caught off guard by its far-reaching effects. But even dramatic changes produce data that can be analyzed and leveraged to better understand business environments; we can support rational decision-making at all levels of the organization, even during a crisis.

In this way, COVID-19 is a wake-up call to companies who have not been able to fully leverage data within their organizations. It’s time to double down on data and analytics. It provides essential instrumentation that will help them navigate future crises of similar scales, and creates an environment of trust across the enterprise.

Self-service analytics that include collaboration, governance, and storytelling capabilities are central to this new paradigm. These capabilities help companies develop and share the insights they need, securing better decision-making capabilities even in remote working environments. Analytics must become the anchor that keeps enterprise capabilities centralized and stable in the future, even as external business conditions evolve.

Easily launch your new self-service solution with Pyramid Analytics

With the right partner, launching a next-generation self-service analytics platform is easier than ever—and there has never been a more important time to adopt self-service analytics capabilities than now.

Pyramid Analytics differentiates itself from other enterprise BI platforms because it was built from the ground up to feature enterprise-grade governance, allowing leaders manage the implementation centrally, without stifling self-service ingenuity. Featuring robust security, collaborative dashboards, and controlled, multi-tenant access for all your business and technical users, Pyramid Analytics provides even geographically dispersed teams with everything they need to drive value-added decision-making. Crucially, it can be deployed in as little as two weeks, and can be scaled to as many users as required.

Contact us to learn more.