I enjoyed Gillian Tett’s “The silo effect: The peril of expertise and the promise of breaking down barriers“. The Financial Times US Managing Director uses a cultural anthropology approach (nice!) to show how strong compartmentalization of expertise made some companies lose their edge while “silo-busting” kept others innovative and adaptive. She uses stories from the worlds of finance, technology, and government to illustrate. And she shows how people, technology and management can help break down specialist silos.
People can help by changing their mindsets, questioning existing taxonomies used to organize the world, or jumping from one field to another. For instance, the Cleveland Clinic gained in efficiency by reorganizing its structure around multidisciplinary centers focusing on body parts or broad ailments (the way patients describe illness) rather than around medical disciplines (the way education segments professions between physicians, surgeons, nurses and therapists). What if we were structured around multidisciplinary teams focusing on, say, age-specific issues?
Technology can help by offering analytical tools that mesh silo data, or facilitating cross-company horizontal communication. For instance, computer analytics from OpenTable was used by the Chicago Police to crunch violence data from different departments with temperature patterns. This generated real-time crime predictions that significantly reduced Chicago’s murder rate. What if we had investigative data science teams to better predict complex issues affecting children?
Management can help by rewarding those who promote inter-disciplinarity, or running internal social experiments that cluster people across specialities (e.g., common induction programmes and staff rotation across disciplines). For instance, Facebook’s Hackamonth encourages staff who have worked on the same thing for 12-18 months to work with a different department for a few months. What if we had a line of stretch assignments that would aim not at filling gaps but rather at disturbing and enhancing teams?

It is always good to have a quick look at the IMF and World Bank’s “curtain raisers” ahead of their Annual Meetings. Christine Lagarde focuses on the economy telling us that it is not looking very good, especially for emerging economies facing a fifth consecutive year of slowing growth. Jim Kim focuses on inequalities in a speech that could have been drafted in NY: importance of investing in children, from ECD to stunting elimination; promoting UHC and progressive social protection; and designing equitable tax collection systems. Fighting inequalities, he says, “starts with the pregnant woman who lives in a conflict zone.” But how does that message trickle down? How much of this rhetoric translates into the World Bank operations in your country?

My map of the week is from the Simon-Skjodt Center for the Prevention of Genocide’s Early Warning Project showing countries most likely to suffer onsets of state-led mass killing. The ranking combines statistical risks with expert opinions, and averages results from 3 “models”: Forecasts of political instability; forecasts of future coup attempts and new civil wars; and a machine-learning process that chews up experts’ opinions. Countries with the highest risks for mass killing today are Myanmar, Nigeria, Sudan, Egypt, Central African Republic, South Sudan, Democratic Republic of Congo, Afghanistan, Pakistan, and Yemen.

My quote of the week is from Quartz Akshat Rathi’s “If there is liquid water in Mars, no one – no even NASA – can get anywhere near it”: “The world’s space powers are bound by rules agreed to under the 1967 Outer Space Treaty that forbid anyone from sending a mission, robot or human, close to a water source in the fear of contaminating it with life from Earth.”