Managers at all levels derive value from tracking key performance indicators (“KPIs”). They use them to monitor major components of business health and, at many companies, to determine incentives such as annual bonuses.
Despite the usefulness of KPIs, there are two main problems with the way they are typically tracked: 1.) It often requires significant manual effort, and 2.) It usually isolates individual KPIs from others and within a discreet timeframe. Performance analytics, on the other hand, adds greater depth to a team’s understanding of its KPIs by making it possible to visualize holistic trends over broad spans of time and to perceive relationships between them.
The emerging analytics approach to KPI tracking represents a true shift in business thinking. To draw a comparison with weather forecasting, the old method essentially attempted to describe a climate from the perspective of a single rainy day within a given month, whereas the new method automatically accounts for the remaining 29 sunny days in the same month. Rather than providing a mere snapshot, analytics
Also Read: Benefits of Migrating to Master Data Management
If you have ever seen KPIs presented in a meeting and wondered how they would look over a different
Here are some dimensions that you may be missing with static KPIs but that are visible with performance analytics:
Performance analytics services can enhance your perspective on the effects that both time and interdependent functions have on your team’s success. This makes it essential to recognize the limitations of your current KPIs and take steps towards telling a complete, cohesive story about the health of your organization.
Once your organization has accepted the need to stretch its KPI strategy to include analytics and has begun implementing an analytics platform, the next step will be to interpret the output of the available reports. Data have little value until they lead to an explanation of what is happening in your business, but that may require a certain level of open-mindedness and sensitivity to nuance.
Here is how a strong performance analytics consulting partner like Trianz can help you fully access the additional depth of meaning available through analytics:
The main difference between standard business intelligence reporting and performance-centric analytics is that the latter focuses on well-defined performance objectives (as opposed to being merely descriptive). When configured correctly, your platform’s presentation of data should be easy to interpret, but we can help you get there.
Also Read: Benefits of Big Data Analytics
Once you have taken the plunge from traditional KPI monitoring into a full analytics approach, you will come to understand the meaning behind your performance analytics services. Only then is it time to start using your data to shape organizational behavior.
If, for instance, you find a strong correlation between a neighboring department’s KPIs and your own, you can form a stronger partnership with that department and use the symbiotic KPIs for shared success. Conversely, if you find an inverse relationship between the KPIs of another team and your own team, you can counsel with the leaders of that time to shift focus and write a successful new chapter for your business.
The possibilities are nearly endless, and our performance analytics consulting experts are standing by to help you take the next step in this journey towards a happy ending for your business.
Contact Us Today
Finding Hidden Patterns and Correlations Innovative technologies such as artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) are transforming the way we approach data analytics. AI, ML and NLP are categorized under the umbrella term of “cognitive analytics,” which is an approach that leverages human-like computer intelligence to identify hidden patterns and correlations in data.Explore
What Is an SQL Query Engine? SQL query engine architecture was designed to allow users to query a variety of data sources within a single query. While early SQL-based query engines such as Apache Hive allowed analysts to cut through the clutter of analytical data, they found running SQL analytics on multi-petabyte data warehouses to be a time-intensive process that was difficult to visualize and hard to scale.Explore
The Cloud is the Key to Transformation Success… Transitioning your applications to the cloud is undeniably a critical factor to a successful digital transformation endeavor. It’s more than just a lift-and-shift, however. Let’s explore several things that you need to consider before migrating your applications to the cloud, including: Readiness of your application portfolio Where to begin – the right business case and migration strategy Technology requirements and considerationsExplore
Application Modernization at Speed and Scale Enterprises are pursuing greater application scalability, cost efficiency, and standardization with containerization and virtualization platforms. So, what’s the difference? Containers are a type of virtualization technology that allows users to run multiple operating systems inside a single instance of an OS. They are lightweight and portable, making them ideal for running applications across different platforms.Explore