The aim of new thinking regarding the storage and use of data is to reuse the data to augment as many processes as possible and, thereby, improve the value gleaned from the data, says analytics multinational SAS Big Data VP Paul Kent.

“The collection, processing, moving, sharing and reuse of data within and beyond the organisation is facilitating new ways of gaining business and serving customers. For example, a large US retailer used parking-lot video data to manage the presence of staff at their tills to serve customers more quickly and efficiently, leading to more traffic through the stores.”

Similarly, data collected by a Philippine mobile network operator to determine customer payment cycles and match offers with their patterns of data use enabled it to get a much more detailed view of customers.

The network correlated football matches with video live-streaming on customers’ cellphones. It then determined whether a customer would use all his or her data prior to the end of the match and provided complementary data to enable the customer to finish viewing the match.

“This is not altruistic, as the company found that it had significantly higher conversion rates by customers whom had been given the complementary data and whom it approached within 20 to 30 minutes after the completion of the match with new subscription offerings or prepaid packages.”

The data was already being collected in both examples, but was reused to support more advanced business uses. The iteration of models and new ways of using data that a company already has are key to improving the value gained from business data, adds Kent.

“The challenge is not that the data is unstructured, but that we should apply a structure to and then use the data to improve various models and use cases. Similarly, we have not thought of all the ways of using the data that we have and, therefore, we should not merely dispose of data for which we have not yet thought of ways to derive value from.”

“Big data ‘lakes’, from which employees on all levels can draw and use data to make evidence-based decisions and create new business models and processes, will stimulate more refined use of data and evidence-led business outcomes.”

Changing the culture of work to include analytics and intelligence systems in many aspects is important to unlock value from data and meet changing business needs.

“We must be comfortable to use and reuse data to gain new answers to new questions that were not asked before,” avers Kent.

A more flexible approach to the use of data has emerged in companies that are more mature in their approach to unlocking value from data. The approach encourages experimentation and small, rapid-iteration projects with well-defined goals, as well as the option to abandon the project early if it is not going well.

“The more experimental mindset is not always suitable, but being more formal in how one approaches and stimulates the use of data in the organisation can help to produce new ways of leveraging data and then making those models more formal and robust.”

While many data initiatives and projects will fail, one project might succeed and provide a good advantage for the company, says Kent. “Many of the wins in big data projects come from data that the organisation already had, but were separate.

Cloud systems and services are well suited to new ways of using data, as they uncouple the processing and application of data from the hardware that companies require.

“Intensive models are not typically run all the time. Often, they are run and then the results are interrogated. Cloud services meet these types of intensive and peak uses without placing an additional equipment and maintenance burden on the company,” he concludes.

Story highlights:

* The reuse of data by companies to augment their business models and processes will help them to unlock more value from their data.
* A flexible and experimental approach to the use of data can stimulate new business uses and provide an unexpected advantage for companies.