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Shifting the business (data) perspective

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James Bell

General Manager, Robinson Ryan

Data management is an accelerator of organisational performance. It’s a tool for executives to better manage an organisation, and improve the way of working across an organisation.

It’s also fundamentally important to get right if your organisation is planning to ‘go GenAI’.


I recently caught up with fellow DAMA Australia board members, Liz Daykin and Andy Peyton, over a coffee and a conversation about how to solve all the data problems of the world. One of the key themes was what #DAMAAustralia can do to elevate how the data management profession is perceived, and the critical work data management professionals undertake across Australia.

Understanding how executives understand data

Liz made the comment that executives inherently understand the importance of data – as consumers of data. Executives live and breathe reports and dashboards, apply analytical skills to interpret, and make decisions based on the data they consume as end users. Data analytics and data science are generally understood by execs. Execs generally are data consumers par excellence.

However, this focus on the outputs of data, and putting energy into better products for data consumers is missing the mark – particularly in a world when #GenAI will fundamentally upend established ways of working.

The process of creation and transformation is as important as the end product

There are few industries where the primary focus is ‘just’ on the final product. From hospitality to manufacturing, executive focus is always on managing the process of production and creation. The ingredients in a Michelin starred meal are carefully sourced, selected, and through carefully controlled process and methods, transformed into an amazing experience. There are very good reasons why the Toyota Corolla was the world’s best-selling car for decades. Toyota was ranked as sixth most valuable brand in the world, ahead of Mercedes Benz.

Toyota, it’s business model and operations, are well researched and discussed examples of organisational success. From jidoka (‘autonomous automation’) to kaizen (iterative continuous improvement), Toyota’s brand is built on reliability. Each element and process are well understood and directly managed. Leaders can and should ensure there is attention to detail throughout the production cycle.

Is it data management or just good business management?

Data management is another management approach to improving organisational operations and efficiency. It’s not an esoteric philosophy. It’s a management tool, one which substantially improves how your organisation runs and what can be achieved. There’s real, demonstrable, and tangible value for organisations who get serious about improving their data management capability. Macquarie is a great example– by reducing their data stores from 8 to 1, they halved their operating costs.

I often talk to clients about data, and particularly where to focus executive attention and energy across an organisation. Data management, and particularly the DMBoK, is an agreed international standard for best practice in managing data. There’s value in examining your current operating landscape against best practice.

Fundamentally, leaders should go back to the source to grapple with the data challenge facing many organisations. Data is created because someone in your organisation did something as part of their way of working. Data management is partly about technology. It’s partly about process. It’s partly about people. The combination of technology, process and people place data management firmly as the ‘way of working’ in your organisation. And this means data should be centred in the sights of your executive attention. Data reported is an endpoint. Unless you understand how that data made its way from the moment of creation into a dashboard or report from the analytics team, you’ve likely excluded the very team that can provide the context on the reliability of the data presented.

The real business risk posed by data

And here’s the glaring business risk – very, very few organisations have perfect data quality.

Data scientists and data analysts are important data professionals. The data they wrangle into meaningful insights requires good business practice be consistently and rigorously implemented and monitored. The data being analysed was managed into a form capable of being reported on. Data management professionals are the bridge between organisational capabilities of technology, people, and process.

Reframe the data perspective – data management is just another way of doing good business. Identifying and managing the right way of doing things. Data management is all about improving process and constantly seeking ways to simplify the technology and data landscape. It’s about creating the right way to do things, and embed better ways of working, identifying inefficiencies and reducing risk.

Better data now trumps rushing into GenAI 

To make the most of GenAI, you need to get your business data in order. Strong business fundamentals are always necessary and will never go out of fashion. Your data is core to your business fundamentals. It is also the greatest risk to your ability to ‘go AI’ in your future strategy. Getting to the AI starting line after strengthening your data management may not be as fast as is desirable, but the long term pay-off to competitive advantage or organisational outcomes will more than justify the investment in time, money, and people. Better data management practices strengthen organisational resilience over time.

Use best practice data management techniques to get the organisation ready for AI. When we say, “best practice data management techniques”, it sounds like a whole new paradigm, which it’s not. Once you start to investigate data issues, you realise that data management solutions are just a better way to run your business. It’s about evolving and adjusting processes, ensuring your people have the right knowledge and capabilities, ensuring the right technology suited to your context, and making sure there is sufficient oversight into what’s going on. It is not esoteric capabilities we are talking about. It’s management and leadership.

Bring your data people inside the tent

Bring your data management professionals into the right conversations EARLY so you can be working on how data can be best leveraged for business initiatives. Find ways to shift the data perspective from ‘data producers’ (“It was fine leaving me”) to ‘data managers’ (“I wonder if the data produced suits the people consuming”). If you can, create a dialogue with those who produce and those who consume the data.

It is an accelerator for success, and proper planning to ‘go GenAI’.

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