The value of data

What is a little four-letter word that can have a big impact on your business? Data.

Collecting data is nothing new, and most large enterprise organisations have been gathering and storing it since their inception. But have they made the most of it? Not necessarily. On the other hand, plenty of businesses nowadays—particularly technology start-ups—have made big strides in the data analysis space as advanced technology has emerged. They are now leading the way to a new age of data management by building systems and products to extract and use data in a way that allows organisations to gain an advantage over their competitors.

So, how can your business leverage its data to add value?

The value of data

There are any number of data points that can be collected from widely distributed networks of critical assets, each with their own potential for value-add. Data can be used to predict future issues and possible solutions, provide a pathway to automation, and improve troubleshooting processes. It can help organisations save money by lowering their operating costs and enabling a competitive advantage. For example, consider the cost savings in an operating environment where routine maintenance is automated. Assets are serviced only when their usage demands it, instead of on a fixed routine. Efficiency increases, because service windows can be predicted, coordinated and scheduled in advance as the condition of site assets change.

Data also comes in many forms. Infrastructure data contains valuable information around power usage, voltage levels, battery health, and the activity of cooling and heating systems. External data can include information about weather patterns or power pricing. Data can tell us if a site is healthy and can be run offline, and proactively assess when maintenance personnel will be required. It can even be extracted from something as simple as a communication received from a customer, generating insights that can be used as part of a customer retention strategy.

Data can also help to attract new customers. After all, if you can demonstrate added value through data analysis and a competitor cannot, you are more likely to secure the project. Just to give you an idea of exactly how much data is really out there, our solutions currently collect around 35 million data points every day for our customers—that is an immense number of insights waiting to be explored.

Barriers to effective data usage

While collecting and analysing data sounds like a fairly straightforward process, it is actually quite complicated. Specific software and dedicated teams are generally needed to efficiently analyse data. Cheaper outsourced resources may not have the expertise or domain knowledge required to make sense of the volumes of data that has been collected. Often then, there are barriers around cost and quality.

This is especially true when you think about organisations storing masses of data in data warehouses; a large telco, for example. In our experience, at this scale, extracting meaningful insights for stakeholders is a huge task. It requires a team with expert resources to efficiently combine and manipulate data to make sense of the data and identify the patterns that have the potential to lead to cost savings and greater efficiency across business operations, which is exactly what accesstel brings to the table.

But if data management is not an orchestrated initiative from the top down it is all too easy to end up implementing expensive systems that employees do not understand or are not trained to use. Once again, the risk is a big financial outlay for little return.

There are also barriers to overcome when operations and IT teams work together, as historically these functions have been kept separate. Without collaboration between these teams, management, and even subcontractors, the chance of extracting the maximum value from data insights is unlikely. But of course, such education takes time and money, and service providers definitely need to be confident in their abilities to sell the benefits of data collection and demonstrate how the initial investment will be outweighed by the value it will bring.

That said, a telco or utilities provider with large infrastructure investments may be hesitant when it comes to data access and analysis due to various risks they associate with these tasks. As we know, mismanagement of data quickly results in a loss of reputation, and breaching legislation such as the Privacy Act can have significant financial ramifications along with the aftershock of a lack of trust from existing and future customers.

It is our preference to approach critical asset management holistically, appointing ourselves as responsible stewards of data when working with our customers. We actively assist them to collect, store and analyse their data in line with best practice security principles. As data experts, we understand the importance of collecting high-quality, contextual data so it can be efficiently analysed to derive actionable insights and add value.

A data-driven future

In order for data analysis to be helpful, there should first be clarity around what needs to be achieved, and context in which the data will be used. Everyone—not just management—needs to buy in to the changes ahead and be made aware of the operational value that data brings to the business.

We think a changed mindset from industry as a whole is needed, so all companies (not just data companies) can reap the many benefits of efficient and responsible data usage. This starts with effective systems and processes in place to retrieve quality data, plus experienced technical expertise gathering insights that fuel business growth. This ultimately means selling the efficiencies of predictive maintenance, automation, algorithms, systems implementation, and change management strategies.

But encouraging organisations to go down the data path is insufficient. There needs to be more education about the implications of not employing a proactive approach to data analysis in a competitive market. And we would all benefit from more discussion and exploration of the benefits of thinking like a ‘data company’ and what it means in terms of business growth and adaptability.