Digital transformation projects are failing in Australia because organisations haven’t linked their data strategy to business outcomes, according to Chris Drieberg, director of pre-sales and CTO for Hitachi Vantara ANZ. Worse still, Drieberg says, the digital infrastructure being built today may prove fundamentally inadequate very soon.

“Most of [our customers] that we deal with today are building a data warehouse strategy and they’ll only look at a data lake strategy when the business is impacted,” Drieberg told Which-50 during the VMware VForum event in Sydney this week.

“So [it is] the old adage, ‘No organisation makes a move until somebody can’t connect to them’. It’s probably too late then.”

To argue his point, Drieberg gave the example of IoT initiatives, expected to grow rapidly in coming years, suggesting too many were already being deployed without clear business goals and not supported by analytics.

“Everyone likes to use the buzzword IoT,” Drieberg said.

“But you can’t automate with IoT unless you’ve analysed your data. And you can’t figure out why you want to automate until you figure out what the business rules are that you want to place on that data, and what insight you want to gain from the data.”

IoT, while not quite taking off at the rate many expected, will certainly do one thing — generate a tremendous amount of new data.

According to Drieberg, that expected influx means the data lake or big data conversation is becoming increasingly common among Hitachi Vantara customers. But another issue is then created – the sheer amount of data can overwhelm an organisation.

Data deluge

The key to dealing with a data deluge, Drieberg says, is to tie data and analysis to business outcomes, or, as other executives have phrased it, “don’t boil the ocean”.

In a Which-50 feature earlier this month, GroupM CEO Mark Lollback conveyed a similar message.

“You can get almost overwhelmed by data and therefore you get almost scared to make a decision because you feel like there must be more data to mine,” Lollback said.

“You should be really clear about what is the question you are trying to solve, and against that question what data sources could give you insight.”

Drieberg agrees, adding a failure to isolate, analyse and use specific data is undermining many digital transformation projects. 

And while linking data to outcomes can help solve data and automation challenges, ultimately digital transformation requires greater organisation wide alignment, including dealing IT back into the conversation, Drieberg said.

Buy-in starts with the c-suite, Drieberg says, but quickly works it way down, and then back up.

“The smartest executives will always take input from their people and develop that [digital transformation] strategy. Because the strategy needs to be aligned to a business outcome.”

Hitachi Ventara’s local CTO gave the example of moving data and applications to a public cloud. Not inherently a bad decision, but one that must enable a business outcome, he said.

“Does [moving to a public cloud] align with our business outcomes? If it does , excellent. But we have to be key with those business outcomes and that needs to be the focus of what we do with our data as well.”

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