Big data is likely here to stay. Most companies, though not yet fully transformed by big data, are at least adapting to it. They are finding innovative ways to apply data science to critical parts of their value chains, and transforming with varying levels of success the ways critical parts of the businesses are run. In this regard, HR currently lags other business functions, such as CRM, in adapting to big data, but is catching up fast, riding a wave of timely HR/IT partnerships.
In the past two decades, HR has attempted numerous reinventions of itself in order to become more strategic, and its investments in information technology are helping to achieve that end. HR’s move toward efficiency and automation of its own operations by means of information technology investments has achieved considerable strategic benefits, including advances in handling and visualizing data, and driving departmental along with organizational transformation.
However, there is still plenty of pain left to address. The “bigness” of big data is both a benefit and burden. As a benefit, it provides a cumulative resource with important properties of being unique, valuable, and non-duplicable, all of which contribute tangibly to competitive advantage. As a burden it requires a significant allocation of other resources to achieve both integration and consolidation.
More is less
Massive amounts of data are being created every year through transactions, customer interactions, surveys, and entries into social networking sites. Yet no organization dare dispose of it. Any combination of data has the potential to reveal critical information about which levers to pull, and by how much. Increasingly, how fast business a reacts to important information determines whether strategic initiatives succeed or fail.
However, businesses are finding that the speed of reaction cannot be accelerated simply by applying more or faster technology. Indeed, the methods companies use to create systems for collecting and storing data simultaneously creates an iron cage that inhibits retrieval and reuse, and is reinforced by the ways organizations try to adapt by creating new categories of data specialists and compensatory tools.
Put in less academic terms, the big data business user has to contend with two tasks that are easily confused: navigating the data (e.g., selecting the right measures, variables, ranges), and the infrastructure in which it resides (e.g., searching and abstracting data from data warehouses, disparate systems). As the complexity of both tasks increase with the accumulation of more data, attempts to simply and include more business users often leads to the opposite result.
The key takeaway is that HR needs to loosen its dependency on IT for data quality maintenance, custom metrics, and workaround applications. Otherwise, inadequate processes that were supposed to be replaced just get repeated once new demands arise. And the result is meticulously collected and stored data remains a seed dead in its husk, not actionable by HR or line managers, never to see the light of day.
