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Give up those Measures and Metrics to Succeed – Really

by Andrew White  |  June 10, 2019  |  Comments Off on Give up those Measures and Metrics to Succeed – Really

I want to comment in an insightful and challenging Opinion piece in this last weekends US print edition of the Wall Street Journal. The article was titled, A Dearth of Data Helped Hong Kong Succeed, and it was written by Jairaj Devadiga.

The article explains an odd fact that Hong Kong’s economic policy management during a period of high growth was correlated with a lack of central (e.g. federal) government planning and that was driven by a lack of data about the economy. For example, GDP was not tracked. The period was between 1961 and 2017, when Hong Kong grew from about a quarter as rich as the UK to almost 40%. The politician credited (in the article) for the low-data; low-federal-government involvement is Sir John Cowperthwaite. He was Hong Kong’s financial secretary between 1961 and 1971.

I found the article most stimulating for a number of reasons. First, I happen to be watching Milton Friedman’s Free to Choose TV series. Hong Kong is frequently references in the series to explore and explain the merits of an economy that is more free-market than what we in the West are familiar with today. In many ways Friedman’s free market ideas are more akin to the level of central planning and federal government involvement we saw in the West before the 1920’. What Milton tells us today (since the 70s, in fact), is that what we call a free market today is not that at all.

The article highlights a dialog between Milton Friedman and Sir John. Clearly the two men are of similar mind. If bureaucrats start to measure something, it won’t be long before they start to meddle in it. GDP and various and sundry economic census data are used as examples, from factory size, turnover, headcount, market share, and so on. The article then compares India’s economic experience over the same period. It seems India’s economic luminaries were more excited with Russia’s example of central planning. India built up a massive central statistical office to track everything, and the central government expanded to start planning more and more. Soon the Indian bureaucrats were picking industry winners and losers. The result was disaster: very low and uneven growth and continued abject poverty.

Looking at the Friedman videos (and book), Hong Kong also still has/had poverty and poor. The difference is that in Hong Kong the individual is freer than in India to make their own changes and improvements, and choices. I won’t at this time shift focus on what Milton talks about when federal programs of welfare are added to reduce the poor – you need to watch his video or read his books to get that.

But let me circle back to data. In data and analytics we all know the phrase, ‘you can’t manage what you don’t measure’. This is a wise management message that we have all taken to heart, what with our love for metrics, KPIs, and performance measures. So how can we square the Hong Kong/GDP story with what we do in the West? Are we destined to operate more like India than Hong Kong? What are the differences here? What are the similarities? Can we apply the same idea to business?

The key might be in understanding what happened in Hong Kong during the period when low central planning and low data awareness were prevalent. Why is it that whatever took place created a fertile ground for high growth with a dearth of data about the economy and subsequent lack of central planing? They key seems to be in the idea that the economy is a self-correcting, self-driving, complex adaptive system. The free market, as extolled by Friedman, assumes the market operates more dynamically and freer than what we see around us. Can our businesses and organizations operate without KPIs? Can our businesses work better if we turn off and away from all our build up performance measures and indicators? I am sure that from the shop floor to the office door everyone would agree wholehearted that this would be good. And I bet every manager and director would turn white with fright if this were possible.

So what would happen, and why? In the case of Hong Kong, the individual entrepreneur, business owner, and worker was as free as anywhere else to find a market, serve it, and maximize their profits. Much of those profits were re-invested to train yet more workers, grow businesses, and start/invest in new opportunities. Would our sales and marketing departments suddenly find a new way of working if we didn’t measure how they worked? Would the supply chain suddenly delivery on time more often than not if we stopped measuring their due date performance?

I think these are challenging questions that are somewhat erroneous. The real challenge is the degree to which the measures we use to influence behavior are aligned to the goals those being measured actually seek. When out measures measure the wrong things, the wrong things tend to happen: all measures are eventually ‘managed’ or even gamed. Measures in fact end up creating new work – to manage the measure! So unintended consequences (part of our global D&A Conference Keynote this year) will almost always take place.

But if we did measure a laudable effort, what happens if that measure still does not align to what the individual wants, what then? The Hong Kong example is intriguing since it did work. So we need perhaps to understand more about what motivates our folks and ourselves. Maybe we don’t need to measure all the low level details. Maybe as D&A leaders we should agree, with our team, the larger outcomes we seek and let the teams work out how they want to measure themselves. Would leaders go for that? I wonder…

If “we” delivery on the outcome, “we” all did real well. If “we” didn’t deliver on the outcome, “we” didn’t do so well. But “we” are all motivated to meet that outcome. Surely the effort would be most efficient if we focused our energies on the outcome, rather than measures that arbitrarily define the outcome (as in GDP for Hong Kong). The Honk Kong example suggests that economic growth will take place almost of its own accord if the workers and leaders were left to their own devices (bar all the arguments you and I might have over the failings of the free market system).

Quite an interesting thought – giving up on our metrics and measures….

 

Category: data-and-analytics  

Andrew White
Research VP
8 years at Gartner
22 years IT industry

Andrew White is a Distinguished Analyst and VP. His roles include Chief of Research and Content Lead for Data and Analytics. His main research focus is data and analytics strategy, platforms, and governance. Read Full Bio




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