Are people the most important variable in your data analytics equation?

5 minutos de lectura 28 mar. 2018

Companies can apply analytics across the value chain, but you need people who can use those insights to make value-creating decisions.

Businesses have long used data to help them set strategy, make operational decisions and manage risks. Now, advanced analytics take that capability to new levels. They create better, faster and always-on ways of finding the profitable, sustainable growth that has been so elusive in recent years.

The big challenge is not to get leaders excited about the potential; it’s turning that potential into reality. Companies have been investing in this area for some time. But those investments too often disappoint.

A handful of CEOs are cutting through the complexity and finding ways to harness the power of analytics. One of our recent surveys, of global consumer products leaders, confirmed that most are still finding it hard to secure value from analytics. However, 11% of the leaders in our survey say that their company is finally deriving actionable insights from all sources of data; 10% believe they can now deliver insights and analytics at scale. And 33% are confident that they can make and implement decisions quickly.

Standing out from the competition

Many companies have appointed a high-level team to study analytics and set priorities for how to apply them across their organizations. They’ve supported those plans with significant investment. But those plans then fail to deliver.

The minority of leaders who are breaking out of that pattern have found the missing piece in the analytics jigsaw. They are winning with analytics because they have achieved the right balance between the technological element of analytics and what we at EY call the “human element.” They have invested in the operational infrastructure that enables them to produce analytics — new technology and tools, data quality and advanced analytics skillsets. But they’ve also paid full attention to the capabilities that enable people in their organization to actually use those analytics.

Companies often fail to achieve their goals because they focus on the former at the expense of the latter. Really it’s about balancing analytics production with analytics consumption. The former covers the technical capabilities needed to create analytics:

  • Infrastructure and tools
  • Controls on data quality
  • Competence in data science

The latter relates to the human factors needed to make the best use of analytics insights:

  • Organization and process design
  • Culture and leadership
  • Embedded learning and development

How to stop worrying and balance analytics

The importance of this human element of analytics can’t be overstated. Companies can now apply analytics at every step along the value chain. They can:

  • Pinpoint their most and least profitable products and customers
  • Optimize their sales forces
  • Sharpen their production forecasting
  • Determine the most efficient routes for their distribution operations
  • Reveal hidden risks
  • Fine-tune their performance incentives

But those improvements are only possible if you have people who can use analytics insights to make value-creating decisions.

Every analytics use case needs a human decision at some point. Data analytics can show how your national supply chain forecast could profitably translate into a series of tactical decisions that drive profitable growth at the store, product or shopper level. But it takes a person to turn that insight into action. The sooner you enable your people to become better analytics consumers, the sooner your investments will pay off. When analytics are embedded in business processes at the point where decisions are made, they generate value.

Every analytics use case needs a human decision at some point.

Humanizing the data

So how can a company get the human element of analytics right? And if you’re in that select group already, how could you build on your success?

  1. Look at how you source and enable the right talent. Identify analytics leaders and embed them throughout your organization, from the corporate level to individual business units, and you’ll be on track to becoming truly data-driven. Make them responsible for designing and sharing repeatable processes that integrate analytics into day-to-day activities and you’ll achieve your goals faster.
  2. Put your analytics experts in key functions where their skills can make an immediate difference. Marketing, finance and operations are likely to be hot locations. But identify the points of greatest leverage for your organization. Support your change-makers with a Center of Excellence and they will become even more effective. This hub would develop central assets for use across your organization, such as data warehouses, technology platforms, data tools and development standards.
  3. Manage ecosystems of partners. This approach gives companies pools of talent to dip into when needed. Some forward-looking companies have put their analytics leaders in tech talent hubs. They monitor new developments in analytics, screen acquisition prospects, and cultivate partners who can help them to access the talent they need.
  4. Build the analytics skills of people who are not analytics experts. The move to analytics-based decision making can be daunting. User-friendly training can get people working with simple analytics tools, making the transition easier. On-site seminars and workshops, off-site education programs, coaching, intensive mentoring by data and analytics professionals – it all helps. Work to demystify analytics and you lessen the fear that can stop people using analytics.
  5. Give people an incentive to change. Reward them with a bonus or a promotion for new recommendations derived from analytics insights. Allow people time away from regular work to develop or follow up new insights.

A question of balance

Analytics possess incredible power and potential. But ultimately, they are just a tool. It’s only when the technological element and the human element — the production and consumption of analytics— are in balance that analytics can deliver. So it’s essential that companies develop analytics as a core competency — not to replace human decision-making but to enhance it.

When people can access information faster and data is easier to understand, the gap between insight and action can melt away. It’s about getting the right combination of art and science. By developing a culture that puts analytics at the heart of everyday business operations, companies can achieve the balance they need.

The question is, can your company afford to short-change the human side of analytics?


No matter how good your data and your tech are, if you don’t get the human element right, your analytics program won’t deliver.

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