Top performing organizations are often led by managers skilled at balancing keen intuition with deep experience in looking at numbers and making hard decisions. Such talented managers value the ability to tell a story with data, and expect colorful, persuasive analysis as a matter of regular conversation, from both their peers and reports. They are astute consumers of cloud technology, and while they may not know all the details, they understand architectures and especially performance capability.
Despite such an impressive skill set, talented managers’ analytical firepower gets neutralized when the information systems they depend on are poorly deployed and excessively complex to use. Even companies with highly quantitative cultures stumble when gaps in analytical skills and culture norms become laid bare, due to tensions about how best to allocate tasks (e.g., collecting and storing vs. retrieving and manipulation), or confusion over who owns the responsibility.
A common example occurs when analytics solutions are built to IT specifications rather than analytical performance objectives. Users who depend on such solutions are frustrated by complex, time-wasting tasks that fall outside their competency sets. Their frustration is confounded by partially successful deployments, which require impromptu learning of ingenious retrieval techniques simply to do their jobs. Some organizations try to rewrite job descriptions so that data analysts must also have advanced IT or database skills, but that only isolates analysts from the business lines and managers.
Even as workforces become more globally distributed, ownership of workforce issues is becoming more centralized in HR, requiring competency in managing the mutability of compliance regulations, the rigor of payroll, and the nebulousness of talent strategy. If that were not enough of a challenge, HR in many organizations is actually winning the argument that it deserves to be a strategic partner with the executive suite, and consequently getting charged with delivering consultative solutions and quantifying impact. Yet with minimal to no methodology in place, even after decades of research in strategic human resource management, workforce problems tend to go unaddressed, left to propagate in size and scope.
Unfortunately, there is no royal road in dealing with this pain point. Technology can illuminate poorly understood, “fuzzy” areas of the business, as well as relationships between levels of the organization, which can help fill gaps or discover complementarities to existing organizational culture. To achieve such insight, many organizations require ready-to-use and best practice methodology, and consulting to help execute their analytics strategy. Combined with good data governance, such solutions can form the core of a successful analytics enterprise, and avoid yet another short-lived analytics one-off that nevertheless ends up taking too much of everyone’s’ time.