Balancing Agility with Control in Analytics Implementations
Most organizations today have some type of analytic tools in use. However, some organizations derive more benefits from these tools than others. These organizations are likely to have an analytically-oriented culture driven by management and characterized by both widespread and regular use of analytics as well as reliance on analytics in decision making.
Achieving this kind of culture begins with leadership by example. Managers who rely on analytics act as champions of such a culture. They often build a cross-functional team of IT and line-of-business representatives that work together to assess and implement the unique analytics requirements that exist across the organization. In meeting the analytics needs for specific use cases, the relevance of the analytics solution is increased and it will grow in use and importance.
Getting the right analytics into the hands of employees who make decisions has nearly immediate quantifiable benefits as both an investment and a set of capabilities available to the entire organization. We see that analytically-oriented organizations are able to increase revenue, decrease costs, and increase agility to better anticipate and respond to market changes over and above competitors that do not have this culture.
When no such culture exists, it can motivate line-of-business departments to adopt their own analytics tools. This may solve a specific business problem in the short term and even foster a broader interest in analytics as colleagues in other groups see effective solutions and then want something similar. It’s a reality that’s not likely to go away, so IT should take a supportive role by helping to guide purchase decisions, assess what functions are needed, and place specific analytics tools in a broader context. These actions can help the line-of-business better understand the organizational analytical strategy that will best meet user needs and also enable IT to focus on its core competencies.
Key requirements for delivering successful solutions include:
- Providing access to multiple, trusted data sources to gain a holistic view of the business versus a myopic view
- Educating and guiding line-of-business on the importance of data governance and working with one version of the truth
- Establishing processes to continually evolve analytics solutions based on rapidly changing business needs. Eliminating costly information silos while meeting changing requirements requires collaboration between IT and business.
IT needs to remain involved in all of these processes. Enabling the line-of-business with self-service analytics that allow them to better control dashboard development spreads the responsibility for meeting user change requests and scales the ability of an organization to be agile. As groups of users become more knowledgeable about the use of analytics, they will seek additional functionality and the IT organization can help find and acquire appropriate capabilities.
As descriptive analysis becomes more ubiquitous, there will be an increased need to perform predictive analysis. Typically, this is the domain of statisticians and data scientists. However, there are offerings now available that mask the complexity of advanced analytics technology by providing tools suitable for business analysts and business users alike. Invariably, new data sources will also need to be analyzed and unstructured content, including text, images, video, and audio, may come into play in certain processes as well.
The emergence of the Internet of Things adds sensor data and the need for real-time analysis to the mix of analytics capabilities that agile organizations will need to address. So while business users may see an immediate need for self-service analytics today, they could be better supported over the long term by a cross-functional team focused on assessing and meeting analytics requirements as they exist today and as they emerge in the future.