Chris Mazzei, Chief Analytics Officer at EY, examines the human challenges of analytics.
In a recent EY and Forbes Insight survey, one-third of executives worldwide said they are striving to build a strong analytics culture. But just as many reported that managers and staff feel threatened by analytics. This suggests that, as in so many efforts to embrace technology-driven change, organizations are focusing on the “hard” capabilities required and neglecting the softer ones, notably those relating to behavior.
In another post on the behavioral dimensions of analytics , I outlined the physical capabilities that organizations should build – technology infrastructure, tools, data scientists – in order to embed analytics into their operations. No less important, however, are the behavioral dimensions of analytics. And developing these assets means tackling essentially human issues. When all is said and done, most analytics use cases still require a person to do something different to obtain value from analytics.
The human challenges of analytics can be separated into two broad categories:
- Macro issues
These are the higher level organizational and leadership requirements that need to be addressed when conceptualizing the organization’s approach to data and analytics. How might the organization’s culture and mental models need to change? What new structures need to be put in place, if any, to ensure data and analytic insights are used most effectively? What resources should be allocated to them?
- Micro issues
These are the individual human behavioral dynamics that need to be considered when designing the application of analytics. Do the ‘consumers’ of analytics have the needed capabilities to make the decisions or implement the business process change expected? Do they feel sufficiently empowered to act and are incentives aligned appropriately??
Where the value lies
Any dysfunction that results from the failure to address these may currently seem limited, since only 17% of survey respondents say that analytics are accessible to a majority of employees in their organization. But almost all automated processes require a human to make a business decision or change a business process, as a result of analytics. When this doesn’t happen, the desired results do not ensue. This means that the stakes will grow as the use of analytics does. There is a direct correlation between how advanced the behavioral and organizational elements of an organization are and the value they are able to derive from analytics. In many ways it is these capabilities that create a value frontier (a ceiling) of what can be achieved.
Real value is delivered to the organization when, with the help of analytics, people change a process or make a decision they would not otherwise have made. Analytics can help a marketing executive to make different decisions around the optimal mix of products and channels; a supply chain manager to act in a more timely manner to adjust distribution network choices; a customer service representative to offer different options for resolving a customer issue; or an internal auditor to focus on the highest risk segments of the business. There are many other examples. But this also demands clear incentives for employees or other stakeholders, to ensure there’s a clear alignment between the desired action and how people are rewarded.
A decisive factor in ensuring that the human side of analytics is fully addressed is leadership from the top – the next theme I will address in this series.