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Straight Talk Technology

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As enterprises continue the buildout of their digital business platforms, there is an increased focus on the role of data in connecting both digitized back-office processes and the digital customer experience. If this next data-driven phase of business transformation is to be successful, organizations must pay greater attention to data platforms, to the automated use of data within their core processes, and to formalizing the use of data in business decision-making.

In enterprise client conversations we see evidence of increasing maturity in awareness and execution of digital programs. There is a realization that outward-facing digital initiatives focused on the customer, consumer, or citizen, must be enabled by digital back-office processes, and organizations typically now work on the front and back office in tandem. The common thread that links these areas is data, with use cases including powering automated marketing, sensing the voice of the customer, optimizing production, and improving recruitment.

Enhanced use of data and analytics has led to greater investment in data platforms, and the development of a repeatable data pipeline (or factory) for generating business insights from raw data on a repeatable and consistent basis. It is essential to continuously evaluate data assets and the data platform in the light of digital business programs, asking questions such as whether key data sources are still fit for purpose, if there are data gaps that need filling, and if the data pipeline needs to be extended.

A particularly important consideration here is that this data will increasingly drive automated, intelligent processes, where the pipeline extends right through from source to action. It’s therefore vital to ensure that data processes are auditable and traceable. There is much discussion on the data ethics considerations around artificial intelligence, and improving transparency within the data pipeline will be crucial to support compliance in that regard, as well as enhancing the quality of business data.

Despite the platform and pipeline improvements, the biggest and potentially most complex change required is cultural. Despite greater automation at a process level, key business decisions are still taken by people. Although the role of data in decision-making has become more prominent, executives (and their organizations) need to make a shift from having to seek out data to inform their decisions, to a mode where they make decisions based on the data that IS the business. This is a subtle but important distinction, which requires all three of these elements (platform, pipeline, and culture) to be working in tandem, and lies at the heart of enabling data-driven business transformation.

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