The most successful companies are those that know how to harness advanced analytical tools. These powerful analytics solutions, whether used in conjunction with self service business intelligence or to create predictive models, can help companies discover trends, patterns, solve problems and accurately predict the future. They can also drive change by using factual information. The analytics solution that you choose will depend on the amount of data and complexity your organization has to deal with, along with what types of business questions you are trying to answer.
Compared with basic analytics, which typically works well with structured data and smaller datasets, advanced analytics can work with both structured and unstructured information and is more appropriate for organisations that have diverse data sources and complex analytical questions. It also has features like dashboards, drag and drop reporting and graphic elements to help business users understand the results of their analyses. It is important to remember that while advanced analytics can offer a number of advantages, it also requires a greater level of expertise and skill than basic analytics.
It’s also important to realize that just because a model makes predictions, doesn’t mean that they will directly influence decision-making. Some of the most successful predictive models take a more indirect route to inform their decisions. This can reduce false positives while improving the speed of converting new insights into strategic action.
While leadership alignment on the value of deploying advanced analytics is critical to supporting wide adoption, survey findings indicate that focusing too much on tactical prioritization, at the level of specific use cases, actually inhibits broad analytic deployment (Exhibit 4). Instead, companies can make more progress by adopting a test-and-learn approach, whereby a team develops an initial predictive model that answers a high-value business question, and then evaluates its performance before moving onto the next use case.
Embracing Advanced Analytical ToolsBy analysing energy usage data from sensors and smart meters, digital platforms with advanced analytics are able to help organizations reduce their energy consumption as well as associated costs. Energy-saving tools can, for instance, provide insight into the likelihood of equipment or machinery breaking down, allowing organizations to schedule preventive repairs and minimize downtime. They can monitor energy prices, allowing for them to take advantage and optimize their purchasing strategies. Additionally, real-time monitoring enables energy-saving initiatives to be constantly monitored and proactively managed, while visual reports on energy usage simplify data interpretation for stakeholders and facilitate effective communication with them. These capabilities can deliver significant operational and monetary benefits to organizations of all sizes.