Machine learning and Big Data will produce the earliest wins for organizations utilizing emerging digital technology, according to Sehida Frawley, SAP Australia and New Zealand head of digital business services. However, she cautions, generating value and confidence in the technology will depend on an organization’s resources, technology ecosystems, and trust.
For example, in order for organizations to trust the outcome of machine learning, they must also be able to trust the underlying data, Frawley said. The trust requirement extends to other technology, like blockchain, where there must be “trust in the relationship of that chain.”
Ultimately, generating value from emerging technology like machine learning, blockchain, and IoT will also depend on resources – how much effort is required to have success – and the technology ecosystems to support new applications, Frawley said. “It’s not just the software, it’s the whole technology ecosystem, and the dependency on that that will drive willingness to go down that path and success in that path,” Frawley said, giving the example of the IoT hardware required to support IoT applications.
The public sector difference
Resources, ecosystems, and trust are common challenges of new digital technology, but the public sector can expect three more, according to Frawley.
The first two factors, risk and value, are directly related, Frawley said. Public sector organizations must weigh the consequences of data use against the value of services it can produce.
“If we go and change how we analyze and react to someone who is doing land tax, are we well informed and what are the consequences to that? So it’s that service provision value proposition that’s different.”
The final factor that is different for the public sector, or at least ratcheted up, is the use of data, Frawley said. In a climate of “heightened sensitivity within public services” regarding the use of data, Frawley says, use should not necessarily follow access.
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This blog was originally published on Which-50