Research and Market Commentaries
In America, the combination of high unemployment and the start of the presidential election process has sparked a great deal of debate about how jobs are created, and lost. Nothing new there. Similar academic and populist debates have been part of every modern recession, as society seeks both strategies – legislation, fiscal and monetary policies – and scapegoats – corporations, machines, trade, foreigners, etc.
Keynes called it the paradox of thrift. During recessions, spending cutbacks by individuals, households and firms are to be expected. Yet, for society overall, this type of mass austerity tends to make the downturn worse. Keynes and his disciples have long argued that the only practical way to resolve this paradox is through substantial government spending. But boosting spending in today's debt-laden western economies requires a big and counter-intuitive bet: that even more debt today will lead to more prosperity tomorrow. Many of us are deeply sceptical, hence our vacillating national leaders.
If you Google the term big data, you will get over 5 million hits. While this figure is nowhere near top-tier buzzwords such as social media (320 million), it is about the same as credit default swaps, and nearly five times that for predator drones. The potential value in analyzing large, and increasingly unstructured, data sets has clearly resonated with the business press, IT suppliers and a growing number of customer organizations.
At our recent Executive Forum in London, LEF researchers and prominent guest speakers – including the author, Clay Shirky; Unilever CIO, Willem Eelman; and Salesforce.com Chief Scientist, J.P. Rangaswami – said a great many important things about the future of Enterprise IT. Technology is clearly moving to the front of the firm, with mobility, social media, business intelligence, and increasingly empowered workforces creating all manner of new challenges and opportunities. While many cost and legacy pressures remain, it's a great time for our profession.
