Rebuilding trust in data through management and strategy

It is imperative that organisations invest in their data management strategy to drive innovation and business transformation.

When the 2016 national Census was published, the Australian media was flooded with fears that the data was too inaccurate to be trusted. Some respondents had dodged questions, others had provided nonsensical answers, and a nationwide website outage meant that a host of time-sensitive responses may have been lost.

But this wasn’t a unique case. A few years on, it seems this lack of trust in big data continues to persist over the business world.

Australian businesses suspect that at least 26% of their customer information is inaccurate, new Experian research shows — just under the global average of 29% (the UK currently sits at 25% and the US at 36%).

With the resounding majority of businesses in Australia (99%) confident that being data-driven gives them a competitive advantage over their contemporaries, this mistrust of the very thing they’re relying on is hugely problematic.

A lack of control over data management to blame

Most Australian businesses surveyed in the Experian Global Data Management Benchmark Report are looking to improve their customer experience, and 85% say investing in data is essential to success in the digital marketplace.

But with 95% admitting that poor data quality is causing detrimental effects for their customer experience, business efficiency and organisational reputation, businesses need to ensure that data management and the lack of control are urgently addressed.

Despite an increasing demand for data and insight, we have not seen organisational data management maturity improve in the past three years — in fact, most companies remain relatively immature in their data management practices. As such, human error continues to be the largest contributor to inaccuracy (50%), which becomes more prevalent with the increasing volume of data.

Other contributors to the lack of trust include: lack of interdepartmental communication (31%), inadequate data strategies (30%) and an absence of relevant technology (26%).

Additionally, challenges such as having a number of different data sources and volume of data (39%) are not going away any time soon; they might get worse as data grows exponentially, flowing from multiple sources, digital channels and disparate systems.

Organisations need to look deeper into managing their data as an asset if the foundation needed (good data) to meet key objectives is to be reliable. After all, trusted data enables businesses to make more informed decisions, foster profitable relationships with consumers, accelerate innovation and gain competitive advantage.

People, processes and tech platforms will pave the way

A third of the research respondents said a lack of trust in data is one of their biggest challenges in leveraging data to achieve top business initiatives. To turn this level of inaccurate information around, it is crucial to have the right people, processes and technology to manage data and make sure it is sound, complete, valid, accurate and reliable.

It’s important to note that trusted data doesn’t necessarily equate to perfect data. But where 100% accuracy isn’t possible, by delving into why data is inaccurate, developing a long-term data management strategy and using the right tools, businesses can create a clear pathway from where they are now to where they need to be to capitalise on their data assets.

1. Assess the data landscape. If you know where data comes from, how it’s used and what the root cause of any data quality issues are, you can build data remediation and monitoring practices that directly address the problem. This helps to build trust and understanding, setting up the landscape for future success.

2. Quick wins evolve perceptions on data management. Momentum demonstrates success. Data management solutions that take months or years will only go out of date and frustrate the business — potentially resulting in a reallocation of funding. Start with the low-hanging fruit, such as benchmarking data quality levels first to get a baseline with data profiling, which can be used later to demonstrate improvement. Then, address easy fixes such as improving data quality at point of capture (customer email addresses are a huge pain point and riddled with errors) or implement sophisticated but rapid time-to-value technologies to remove duplicates and consolidate databases.

3. Invest in the long term. While the C-suite certainly understands the importance of data and the potential insight it can bring, it isn’t always matched with the required investment to manage that information over time. Often, organisations approach data management from a technology-first perspective. Data governance is seen as a once-off, finite project, and it’s believed that buying and implementing the tech will make issues go away.

However, what is needed is a long-term strategy that looks into how information can be improved and maintained over time and most importantly should look to include bite-sized projects within the wider game plan to maintain momentum with continual wins. This may also include organisational shifts to make processes more data-centric, and hiring the right data talent.

Developing trust is a journey

We live in the era of data explosion and disaggregation. Data is a strategic asset that can help organisations not only gain a competitive advantage, but also improve operations and provide a better experience to their clients. But this is only possible if we trust the data at the foundation, and the processes and people who are governing it.

It is imperative that organisations look at investing in their data management strategy to drive innovation and business transformation. Developing trusted data is an ongoing journey and everyone in the business has a part to play and, therefore, a level of accountability.

Pictured: Steve Philpotts.

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