by Thor Olavsrud

Executives still mistrust insights from data and analytics

Nov 02, 2016
AnalyticsBig DataBusiness Intelligence

Organizations say they are increasingly focusing on data-driven decision-making to guide their businesses, but a majority of business leaders lack confidence in the insights generated from data and analytics.

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Data and analytics are increasingly becoming central to business decision-making, especially in areas such as driving customer growth, improving productivity and managing risk. But even as organizations push to make their decision-making more data-driven, business leaders accustomed to making decisions based on gut-instincts and experience are having trouble trusting insights from data and analytics (D&A).

Forrester Consulting, commissioned by the Data and Analytics Global team at professional services firm KPMG, recently surveyed 2,165 data and analytics decision-makers from a range of industries in Australia, Brazil, Canada, China, France, Germany, India, the U.K. and the U.S.

Still a matter of trust

Forrester’s study found that 50 percent of businesses use data and analytics tools to analyze their existing customers, while 48 percent use them to find new customers and 47 percent use them to develop new products and services. Even so, the study also found that executives exhibit a distinct lack of trust when it comes to data and analytics: 60 percent of respondents were not very confident in their D&A insights.

Only 10 percent of respondents felt their organization excels in managing the quality of D&A. Thirteen percent felt they exceled in the privacy and ethical use of their D&A and only 16 percent said they believe they perform well in ensuring the accuracy of models they produce.

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“As analytics increasingly drive the decisions that affect us as individuals, as businesses and as societies, there must be a heightened focus on ensuring the highest level of trust in the data, the analytics and the controls that generate desired outcomes,” Christian Rast, global head of D&A and a partner with KPMG in Germany, said in a statement yesterday. “Organizations that continue to invest in D&A without determining its effectiveness could likely make decisions based on inaccurate models, which would perpetuate a cycle of mistrust in the insights.”

“Failing to master analytics will not only make it increasingly hard for organizations to compete, but will expose their brands to new and growing risks,” Rast added. “Seventy percent of executives believe that by using data and analytics they expose their organizations to reputational risk.”

Executives felt most confident about the insights they glean from data and analytics around risk and security, though only 43 percent said they’re very confident about those insights. Only 38 percent said they were very confident in customer insights and 34 percent said they were very confident about insights into business operations.

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“There is no doubt that subjective, gut-feel decision-making is being augmented by data-driven insights to allow organizations to better serve customers, drive efficiencies and manage risk,” Bill Nowacki, managing director, Decision Science, KPMG in the U.S., said in a statement Tuesday. “The survey, however, indicates executives’ level of confidence in their insights is not where it should be, given these organizations’ plans for increasing investment in and returns on D&A.”

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:

  1. Assess the trust gaps
  2. Create purpose by clarifying goals
  3. Raise awareness to increase internal engagement
  4. Develop an internal data and analytics culture
  5. Open up the ‘black box’ to encourage greater transparency
  6. Provide a 360-degree view by building ecosystems
  7. Stimulate innovation and analytics R&D to incubate new ideas and maintain a competitive stance
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