Family businesses looking to innovate might like this example of corporate venturing. Kuehne + Nagel, the huge Swiss logistics firm that’s majority owned by the Kuehne family, has launched a new company, designed to take advantage of a large amount of trade data the business generates.
Called LogIndex, the company was started last year to commercialise the global Kuehne + Nagel indicators, or what the Swiss company says are gKNi (global Kuehne + Nagel Indicators). “The development of gKNi and creation of LogIndex are results of a corporate venture of Kuehne + Nagel and is 100% owned by them,” says João Monteiro, managing director and founder of LogIndex. Monteiro says LogIndex now has five customers, including a global bank.
“The data service we sell is a derived data set created from the Kuehne + Nagel anonymized and aggregated data plus logistics data from 55 different sources e.g. real-time vessel and jet positions. In total our models work with more than 25,000 time series of input data, several of them in real time,” says Monteiro.
He adds that the data often proves much more accurate that “street” data, i.e., median of the consensus of surveyed banks available. Monteiro cites in support of their data recently released numbers on China’s balance of trade, with the LogIndex/gKNi data more accurate than the street estimate.
Rado Lipus, founder and CEO of Neudata, which scouts new and interesting datasets, and connects data providers with hedge fund and asset management clients, says there is strong demand for big data from family businesses and family offices.
“The data monetization opportunity for many family office/family businesses to the financial sector is in several millions of dollars of recurring revenues,” he says. “And in rare cases in tens of millions of recurring revenues. It is particularly valuable if the data source is unique, has granularity, and its timeliness is high.”
Lipus adds that businesses don’t need to be big to have valuable data. “I think the key is that the data, from large or small businesses, provides something new or different. The data has to be of good quality – the key is how clean is it, consistency, history, length, data frequency (hourly, daily, weekly etc), and how compliant it is.”