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Innovating Your Enterprise Data Strategy: Three Key Takeaways

As technology and innovation becomes more complex within the enterprise, the amount of data organisations collect and use is growing…

By Anthony Bell , in Disruption and Innovation , at May 21, 2019 Tags: , ,

As technology and innovation becomes more complex within the enterprise, the amount of data organisations collect and use is growing exponentially For an organisation to remain competitive and customer-focused in today’s world, it’s vital to ensure data is fit for purpose and enables good decision-making. In this way, chief data officers and information leaders must develop a holistic framework for collecting, analysing, storing organising and sharing that data in a secure way that meets the principles of good data governance.

The executive luncheon, Innovating Your Enterprise Data Strategy: Building a Responsive Framework to Drive Growth and Innovation, hosted by Informatica and Innovatus Media at Melbourne’s Vue de Monde, looked at how it is essential to improve data quality to enable their organisations to become more customer-centric. Along with developing the right platform, the discussion also explored the importance of good data governance principles.

Reflecting on the robust and candid discussion, here were the three key takeaways from the session:

Data Quality is the Real Quantity

Informatica’s Managing Director for ANZ Nick Smith noted:

”Data quality must be fit for purpose. I always ask the question: “What are you going to use this data for?” to ensure their actions regarding data quality align with their needs.”

Data quality, Smith continued, is intimately tied up with the user of that data.

“It’s important to understand that sometimes the user will receive data that they don’t need – which is not a best practice as it not the most efficient way to use data. Over the last decade, many enterprises have undergone mass-data transformation efforts aimed at creating data lakes, achieving a single customer view, as well as integrating data from both inside and outside the business.”

The challenge posed with this strategy is that data is only valuable in the hands of the right executive, and some data is more critical than others. This former idea will become critical as data continues to proliferate; businesses will start to consider the quality as opposed to quantity.

One participant stressed that it’s important to help the C-suite understand the cost to the business of not getting data quality right in order to sell the benefits of data governance. He said: “in many cases, BAD business decisions are made based on GOOD analysis based on BAD data.”

Another participant agreed, saying: “in the modern data world, there is no room for not having data governance.”

Security is at the Forefront

The next wave of business transformation will revolve around securing the “digital business.” Smith and the group expressed that data quality could else lend itself to another important component of driven and innovative data strategy – security and privacy.

With 40% of breaches that were exposed by the Australian Government’s new notifiable data breach scheme involving the sharing of data by an individual within a company to an outside source, building a data-strategy with secure guardrails is critical when looking at good data governance.

“We advise organisations about the responsibility of securely sharing, accessing, and collecting data. It is easy to bring down the carefully built reputation of an organisation with one data breach, so it’s important to get this right now to ensure your data strategy matures with growing customer and regulatory expectations,” Anand Ramamoorthy, Director, APJ Head of Data Governance and Data Security at Informatica noted.

Platforms for Artificial Intelligence Need Development

A critical talking point from the session was looking at how emerging technologies, such as artificial intelligence (AI), will have an impact on data management and analytics strategies.

While most of the executives stated they believe AI is in its early stages of development, the consensus was that systems need to be prepared to explore and exploit the benefits of AI exploration.

“There is a lot of appetite from the business for AI, but we need to have the right systems and processes in place to take advantage of these innovations,” one attendee noted.

The success of AI projects lie within getting good data quality and governance from the onset. Otherwise, the data itself will likely contain inherent biases and engender weakness within decision making and future learning of the system.

A Burgeoning Space Within the Enterprise

All 15 business leaders in attendance have roles that look at data analytics and governance. These roles will continue to rise in importance within the C-Suite ranks, as business leaders continue to shape leadership teams that build strong futures for their companies. 

Although challenges of integration, security, and driving innovation with data exist, it is important to consider the outcomes that can be achieved with investment and development, something that all of the executives were motivated to see.