How Can Business Leaders Maintain Trust Across the Analytics Lifecycle?

November 16, 20168:06 am601 views

Most business leaders today believe in the value of using Data and Analytics (D&A) throughout their organizations, but say they lack confidence in their ability to measure the effectiveness and impact of D&A, and mistrust the analytics used to help drive decision making, according to a new survey from KPMG International.

For the report, Building Trust in Analytics, KPMG commissioned Forrester Consulting to survey 2,165 respondents from 10 countries to identify in which areas businesses are using D&A, and to what extent they lack trust in their D&A models and processes to drive decision making and desired outcomes.

The report shares insights and recommendations on suggested processes, practices and governance for building trust in D&A using KPMG’s four anchors of trust – a framework for assessing quality, effectiveness, integrity and resilience. Most businesses use D&A tools to analyze existing customers (50 percent), find new customers (48 percent) and develop new products and services (47 percent).

Yet, executives do not trust that they are managing their D&A processes effectively to generate desired outcomes and lack the necessary measures to assess the efficacy of those models.

“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,” said Christian Rast, Global Head of D&A, and a partner with KPMG in Germany.

“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.”

Rast continued: “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. Seventy percent of executives believe that by using data and analytics they expose their organizations to reputational risk.”

Low levels of trust may filter from the top down – confidence lacking in key areas

Just under half of respondents are very confident about the insights they’re deriving from D&A in the areas of risk and security (43 percent), for customer insight (38 percent) and only one third are very confident about their insights around business operations (34 percent).

“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,” said Bill Nowacki, Managing Director, Decision Science, KPMG in the U.S. “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.”

These low levels of trust may originate at the top and filter down through the organization, the survey data suggests. Nearly half of respondents report that their C-level executives do not fully support their organization’s data and analytics strategy. This low level of confidence points to a lack of trust in the insights generated by D&A, which may be due to D&A’s inherent complexity.

See: Balancing the Promise and Pitfalls of Human Capital Analytics

“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,” said Brad Fisher, D&A leader, and a partner with KPMG in the U.S. “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 Four Anchors: Managing Trust across the Analytics Lifecycle

A closer look at the analytics lifecycle reveals gaps in trust. Trust is highest at the beginning of the lifecycle – data sourcing – and drops significantly thereafter. According to the findings, 38 percent of respondents have the most trust in data sourcing, which is determining which data is relevant for analysis.

Twenty-one percent have the most trust in the second stage, analysis and/or modeling; and 19 percent have the most trust in the third phase, data preparation and blending. Trust slides dramatically at the fourth and fifth stages of the lifecycle. Only 11 percent have the most trust in using/deploying analytics and 10 percent said the same about measuring the effectiveness of their analytics efforts.

“This drop in trust indicates broader challenges associated with teasing out insights generated from analytics,” said Fisher. “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.”

Here are some recommendations for organisations to close the trust gap across the analytics lifecycle:

  • Assess the trust gaps carefully
  • 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
  • Have a 360-degree view by building ecosystems
  • Stimulate innovation and analytics R&D to incubate new ideas and maintain a competitive stance.

“It’s imperative that data and analytics leaders make trust a high priority,” Rast continued. “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.”

Also read: HR Transformation Initiative for 2016: Technology and Analytics in Focus

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