Illuminate The Road Ahead With Embedded Analytics Solutions

Recent advances in embedded analytics technology have tremendous upside potential for businesses and organizations who want to use data to make better strategic and tactical decisions.

Simply defined, an embedded analytics technology is any integration of analytical tools within an applied business process or workflow.

Common applied examples include:

• A weekly financial report produced for your executives
• A visualization of your sales team’s progress toward quotas
• A filterable dashboard of the best inventory to buy right now
• A virtual assistant that handles repetitive tasks at certain times
• Many specific instances and use cases still awaiting invention

The substance, or content, delivered to users by embedded analytics technologies broadly falls into a few different categories: intelligence, notifications, predictions, and automations. Let’s explore these a little further:

• Intelligence, generally speaking, describes things that have already happened. Perhaps how many widgets the company sold last month, or the average cost of financing on new inventory. Could even be a custom historical metric of your own creation. Think of intelligence as you would the box score on last night’s game, or a public company’s quarterly earnings statement. Also, beyond raw numerical counts and statistics, intelligence can be qualitative, aggregating information from the web, collecting news clippings, or reporting popular keywords.
  
• Notifications are about actively unfolding or near-current events. When the smoke alarm goes off in your home or workplace, it’s conducting the function of a simple analytic system: collect data, assess conditions, provide feedback. The same is true for alerts in a digital context, wired up to your business systems, notifying you when a specific circumstance has occurred.
  
• Predictions in this case aren’t directly human estimations, but rather the outputs of predictive analysis performed by scripted software running computer models trained to assess statistical probabilities on provided inputs. Based on the data fed in, these advanced analytics systems present users with information about what to likely expect, or what choices might be advantageous given conditions. An example of this category that’s been around for awhile is weather forecasting — think of these embedded systems as reminders to pack a jacket or umbrella.
  
• Automation in a physical sense can refer to robotics and hardware, but in the context of analytics, we’re talking about the use of data and information in the cloud to automatically trigger events and scripted processes that eliminate what used to be a manual task. Instead of an employee needing to routinely rebuild a spreadsheet report each week, an embedded analytics solution can be configured to build the file itself and email it to executives or serve it to users through a portal or dashboard.

Exactly how are these tools valuable?

• Intelligence — Accurate and consistent information about prior events is absolutely crucial to owners and executives who plan and execute business strategies. Making the right decisions, or even knowing what questions to ask, relies on an informed understanding of what has happened and what the present conditions are. Embedded analytics platforms enable BI and reporting that can (1) scale without significant overhead labor costs, (2) be updated more frequently with more current information, (3) more securely and confidentially process sensitive data and insights, and (4) facilitate more holistic and strategically-aligned reporting through metrics calculated from multiple underlying data sources.
  
• Notifications — The value proposition behind analytics-driven alerts and notifications is similar to that of intelligence, but is more specifically focused on speed and responsiveness amidst execution. Alerts are often implemented in more tactical use cases, though that doesn’t make them any less impactful: reacting faster, and with better information, can be worth untold amounts depending on the situation. Notifications also give us logs, or a sort-of time-stamped “paper trail” that can be analyzed in aggregate to spot patterns in activity or outcomes.
  
• Predictions — Predictive analytics have been brought into mainstream consciousness by films like Moneyball and sites like FiveThirtyEight. Initially developed in economics and the finance industry, these methods are widely used in the largest global enterprise settings, and throughout the scientific community. The value, of course, is in the idea that a data-driven model can outperform unassisted human judgment, particularly in areas where humans are exceptionally prone to bias or struggle to ascertain all the underlying facts and data. But, like the weather report, these predictive systems aren’t always spot-on. It’s important to have adopted a coherent data strategy, and mastered the historical and real-time analysis, prior to jumping to this advanced (albeit quite powerful) level.
  
• Automations — Unlike predictive tech, automation solutions are often actually among the most achievable for small and mid-sized firms, and the value they provide is the most straightforward. When employees are freed up from repetitive tasks like report building, they can focus on applying their time (and your labor costs) toward more meaningful, value-added work doing something else. Risk is also a key consideration here, as there are very real costs to having data handled manually when it comes to controlling the security, integrity, and all-around governance of your organization’s internal data.

Common Embedded Analytics Use Cases

So let’s get more specific. As a category, embedded analytics spans a wide range of business and technical use cases, and the market is full of products tailored to individual industries and use cases. Some practical examples include:

• Executive Dashboards
• Data Visualizations
• Operational Reporting
• Financial Reporting
• Self-Service Analysis
• Workflow Guides & Tools
• Operations Alerts
• Proprietary Products

What do these solutions all have in common?

Remember, embedded analytics are the integration of analytical tools within enterprise systems or workflows. This necessitates an advanced technical architecture, which major cloud platform providers now make affordable to businesses and organizations of all sizes.

Your CRM, DMS, ERP, or other system may already have some analytics and reporting features built-in. But those tools are limited to calculations made with the data contained within them. Your marketing platform can’t give you insights that account for what your sales team is doing in the CRM unless you manually or specifically integrate them somehow. Embedded analytics platforms centralize data across platforms, maintain the consolidated data in ways conductive to data integrity and analysis best practices, and make that data, in many different forms, available to applications “downstream” of these data management practices.

The nature of this extensibility is meaningful too. What you extend from an integrated data store, into other applications, report generators, and event-based systems must be strategically designed, structured to facilitate not just what you need to substantiate current reporting and analytics efforts, but what might be useful to analysis down the road. Likewise, alerts and other actions triggered by reported data must be served the inputs they are programmed to use.

Interested in learning more about how we can put embedded analytics to work for your business or organization? Let's find a time to talk.