As big data analytics moves beyond a buzzword in marketing circles, global enterprises are now also starting to see the potential value of turning analytics inward, to improve their own operations, says Ayanda Dlamini, business development manager at LGR.
When enterprises first assess the potential for analytics tools, their common response is to focus on its potential for better understanding its market, targeting services and product releases, and reacting in almost realtime to changes in the environment. Analytics certainly delivers unprecedented abilities to know and understand customers and manage their current and future expectations more intimately.
However, analytics can do a lot more than look outward. When turned inward and focused on business operations, analytics has the potential to revolutionise operations across the board, allowing management to streamline the business, identify trouble spots, better allocate resources and improve the enterprise’s cost-efficiencies. Competitor analysis can be carried out more effectively when the enterprise has a clear view of both its own and its competitors’ operations.
The beauty of advanced analytics is that it allows us to identify patterns and trends that would not normally be apparent, even going so far as to allow us to predict future patterns and trends and take proactive steps in line with these predictions. For the first time, enterprises are given a clear view of what is really happening within their operations.
A Beye Network research report prepared for LGR partner, Oracle, noted that most organisations have large volumes of historical data within their repositories, but that typically, they store this data and never use it to improve their actual business.
The report said that operational analytics gives enterprises the ability to accurately determine the cost of procedures, likely risks and high value focus areas. It allows enterprises to embed collective intelligence into systems, reducing the impact when experienced staff members leave the company. Critically, it allows the organisation to improve customer experience through more effective products, solutions, service delivery and response times.
However, the report noted that not every analytics technique or technology is appropriate for operational analytics. In addition, many organisational cultures are resistant to moving from making decisions based on “gut feel” and experience to making decisions based on data alone. Learning to “let the data speak” requires a mind-set shift – particularly among senior and experienced staff, the report said.
The report also noted that flexibility was key to project success, with initial deployments often having to evolve due to changing circumstances.
Successful organisational analytics projects are generally supported by strong organisational change, with initial projects very focused in their scope and the business decisions that were to be made using the analytics, until the new methods have proven themselves. Once initial projects showed success, the report found, acceptance grew and more opportunities were identified for organisational analytics projects.
The extract, transform and load (ETL) tools employed need to be able to handle, apart from relational data sources, telecommunications native data; extracting this data from its raw form, cleaning, normalising. In near real time, this data is to be loaded, merged and enriched with data from other sources (internal and external) to present and correlate insight.
In the telecommunications sector alone, we are witnessing telcos effectively using operational analytics to make more effective use of their networks and resources, enhance fault reporting and maintenance, to discover churn factors and predict churn, predict demand and take proactive steps accordingly, as well as design and deliver products and services that are more accurately targeted to meet their customers’ needs.
While telcos may be facing declining revenues on traditional voice and data services, they are successfully reducing their operating costs and expanding into new business areas supported by effective, advanced operational analytics tools. The potential for business improvement through the use of advanced and predictive analytics is just as great across all industry verticals.
Data is a company’s biggest strategic asset, and to maximise its potential, enterprises need to revisit their data management, data warehousing and analytics capabilities and start trusting what analytics can do for their operations.
