C-level executives must support the data and analytics
The survey data suggests that the lack of trust in data and analytics may start at the top of the org. chart and trickle down. Nearly half of respondents said their C-level executives don't fully support the organization's data and analytics strategy. Brad Fisher, US D&A leader and a partner with KPMG in the U.S., suggested that the complexity of data and analytics, and the lack of transparency into what drives the insights derived from them, plays a role in executives' mistrust.
"Transparency about the use and impact of an organization's data and analytics is key to overcoming the long-held bias that conventional decision-making is more reliable," Fisher said in a statement Tuesday. "We need to take D&A out of the 'black box' to encourage greater understanding about its use and purpose to help organizations trust the new insights it can bring."
The survey also found that trust in analytics varies along the analytics lifecycle. Executives had the highest trust at the beginning of the analytics lifecycle — data sourcing, which determines which data is relevant for analysis. Thirty-eight percent of respondents had the most trust in data sourcing. Twenty-one percent had the most trust in the second stage: analysis and/or modeling. And 19 percent had the most trust in the third phase: data preparation and blending. From that point, trust fell dramatically: only 11 percent had the most trust in using/deploying analytics and 10 percent said the same about measuring the effectiveness of analytics efforts.
"This drop in trust indicates broader challenges associated with teasing out insights generated from analytics," Fisher said. "Merely being a data-driven enterprise doesn't cut it. To drive trusted insights that deliver value, organizations need to do the work upfront — mapping out the desired outcomes and devising the necessary plans, processes and metrics to ensure effective execution."
With organizations investing heavily in data-driven insights and decision-making, Rast said it is essential they determine where trust in the analytics lifecycle is lacking and then work to close those trust gaps.
"It's imperative that D&A leaders make trust a high priority," he said. "To be a competitive, D&A-driven organization, business leaders must navigate the complex processes, systems, compliance requirements and governance to confidently and consistently move from insights to measurable action."
KPMG recommends organizations address seven key areas to close the trust gaps:
- Assess the trust gaps
- Create purpose by clarifying goals
- Raise awareness to increase internal engagement
- Develop an internal data and analytics culture
- Open up the 'black box' to encourage greater transparency
- Provide a 360-degree view by building ecosystems
- Stimulate innovation and analytics R&D to incubate new ideas and maintain a competitive stance
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