Delivering Doable Data Strategies - Catherine Lopes PhD
Considerations for APAC data professionals wanting to jump in the deep end of major data and analytics projects
Plenty of business leaders and analysts will say that organizations in Australia and New Zealand get hyped about new technologies and are ardent when it comes to adopting the next best thing, particularly when it comes to big data and artificial intelligence.
While it’s a good thing to be keen to invest in new technologies and capabilities, the foundations of new capabilities don't always come easily. This is why we hear so many data and analytics specialists talk about the importance of foundational data governance and an end-to-end data strategy.
Catherine Lopes PhD has spent some 20 years in the data and analytics space and seen the whole spectrum of data and analytics strategies in action, from building foundational data governance and gathering business intelligence, to developing advanced analytics and implementations of AI.
Dr Lopes, who will be speaking at Corinium’s upcoming CDAO Deep Dive: Data Innovation Online A/NZ event, has seen first-hand from inside Australian organizations the challenges that arise when data and analytics projects become part of the executive agenda.
Prior to finishing up a stint at ME Bank in June to focus on her consulting business OpsDo Analytics, Lopes held senior data and analytics roles within ANZ Bank, PwC, and AGL, among others.
Having contributed to the recent report, State of Data and Analytics in Australia and New Zealand 2021, Lopes spoke further to Business of Data to discuss the maturity of the market in ANZ and the considerations organizations getting advanced data projects off the ground should make.
In no small part helped by COVID-19, Lopes is seeing demand for data and analytics expertise within organizations rise quickly, and is determined to help her customers make the right decisions when implementing an appropriate data and analytics strategy.
“COVID-19 had accelerated the shift to data and analytics and organizations realize they need insights from data quickly,” she says. “This can be challenging for companies that quickly jump into a data project without a data strategy. Without a data strategy, there is no resilience built into systems that deal with data that is constantly changing.”
Lopes, who has worked in the United States and was also a contributor on the recent report, State of Data and Analytics Australia and New Zealand 2021, says when it comes to the maturity of the sector in the ANZ region, there is some noticeable lag.
“I returned from working in the US five years ago, after stepping back into data and analytics roles here and doing a quick review, I would say we’re about five years behind,” she says. “And in the time since, I think that gap has remained consistent. However, we are very early adopters of a lot of new things which is really positive.”
Looking to the broader Asia Pacific market and focusing on Singapore, Hong Kong and China, Lopes says the gap between them and the US in terms of data and analytics may be similar or slightly bigger, but there are some positive caveats to that determination.
“They are pushing really hard to consolidate their foundations in terms of getting the infrastructure right, and getting the data into the cloud and making it more accessible and manageable,” Lopes says. “They are also pushing that front part of the journey, foundational data governance and quality. While the middle part, being dashboards, reporting or BI, they are quite mature already.”
While having well-developed dashboards and BI capabilities in place is a positive, those insights will be subpar if good governance and resilience is not in place, which is where Lopes says one of the Asia Pacific region’s big challenges sit.
“Right now, I don’t see much evidence of organizations working out appropriate strategies to tackle this and that’s perhaps why this market may be lagging behind,” she says.
The Importance of a Complete Pipeline
Organizations in Australia and New Zealand are eager to adopt new technologies, but time and time again we hear data and analytics professionals strongly advocating for more attention to data governance and quality.
Lopes has seen this first-hand and says she has spent a lot of time getting people on the business and technology sides of businesses educated on the importance of an end-to-end strategy and integration of technology and business process.
“When I got back to work here, I was focused on advanced analytics, getting business adoption and pushing that a data strategy was needed,” Lopes says. “Everybody was talking about having a data lake. However, businesses will not see the value until they have models to productionize and put technology enablement around these processes.”
In roles at AGL and ME Bank, Lopes says she built comprehensive one-year and three-year data strategies to cover the end-to-end data and analytics journey.
“I realized though that the scope of what is needed for organizations here is much broader. You have to have the entire pipeline and the entire ecosystem thought out,” she says.
“Data and analytics transformation is not an easy task on the enterprise level. From the technology angle, data transformation needs to carry the encumbrance from outdated legacy systems and challenges from fast-evolving technologies at the same time. On the other side from the business angle, analytics needs to strike a balance between the dynamic of changes in customers demand and the internal processes adaptation.”
Like many data and analytics leaders, Lopes is conscious of the skills dilemma involved when organizations decide they would like to turn on a transformational data capability.
“We are good in terms of our openness to technology, but there is an important people and skill component, where we perhaps lack a level of technical depth compared to the US and other markets,” she says.
“We do have many leaders in business and technology saying, ‘Hey let’s get onto this’, but without the technical experience and domain knowledge of business adaption, we have seen many projects, especially AI projects, fail. To convert a pilot into programs that actually deliver measurable business value, we need a cross-functional team with technical skills and business expertise!”
These are among the challenges Lopes will be focused on helping organizations through her consulting firm, OpsDo Analytics, which will specialize in data analytics strategy development.
“I’ll be providing advisory services to help clients with challenges that might including building a data, analytics or AI strategy, developing data capability and operation models, developing use cases for data and AI use, data migration and cloud transformation, and data culture,” she says.
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