Harvard: data-led competitive advantage not so clear cut
A recent article in Harvard Business Review argues how hard it is, contrary to popular belief, to build a lasting competitive edge using learnings from customer data. The thinking goes like this:
- Companies built on data have been around for a long time, and using customer data to make products or services better is indeed an age-old strategy…
- Rather, the “new” news is how fast we can now process and make sense of vast amounts of data. We have machine learning, cloud and marketing technologies of all sorts to thank for that...
- By the same token, the ability to derive learnings from customer data of all types, at speed and in volumes never seen before, doesn’t guarantee any business a robust or durable advantage, the argument continues. After all, using such learnings to improve products is fast becoming the norm across industries and so, is hardly differentiating...
- Instead, the piece concludes, for businesses to thrive and last, learnings must be based on data that 1. provides a high and lasting value-add, 2. is proprietary and leads to improvements hard for others to copy, or 3. creates network effects…
Simple enough. Or perhaps not.
The assertion that customer data doesn’t confer any sustainable advantage without meeting certain criteria isn’t surprising. Assuming that businesses are equipped to make the most of their data to begin with, is however.
Fundamentally, not all markets and businesses are equal.
The “data-smart” businesses referenced in the article are mostly American and global. From beloved household names such as Pandora or Google to the more obscure ones such as Mobileye owned by Intel. HBR is American too, which arguably explains its somewhat US-centric view of the world. Regardless, one can’t help wonder how Australian businesses compare in the data race.
Reflecting on my experience working on data projects for Australian organisations, that level of data sophistication appears to be the exception rather than the norm.
Whilst Australian businesses show great appetite for all things data to drive growth, their ambitions are seldomly matched with the necessary resources. In truth, talent, technology or financial resources are often lacking to effectively connect, mine and derive value from their customer data sets, and turn them into both a powerful revenue driver and durable differentiator.
Very few also have the scale to support such endeavours (e.g. the ability to tap into a central data science team out of HQ). And when they do, they aren’t always able to access or operationalise their own market data (e.g. managed or controlled by HQ overseas).
Another recurring scenario has been a dependency on external experts to help fully realise their data potential. The increased reliance on outsourcing vital aspects of the business “data engine” is in part due to a shortage of specialist talent. Also, with marketing technology becoming increasingly complex, for some, it’s easier to get the vendor and other specialists back in to help out rather than try to keep up with it all.
Understandably, customer data is the holy grail for many. Yet, it’s only one part of the equation.
Customer data generated within the organisation’s “walled garden” (e.g. CRM or sales data) is an essential source of truth, but not the only one. There are other sources, readily accessible and easier to mine, that businesses should always consider regardless of where they are on their data journey.
For example, online conversations are one such source. The key here is to look for signals not just inside but also outside the brand ecosystem (e.g. open-source web data or forums), to help uncover extra nuggets of information about the brand, products or competitors. Search behaviours are one other valuable source of insights, to discover what customers really want and aren’t always telling you.
These are just two non-proprietary data sources amongst others that may be explored in support of a market assessment and differentiation strategy.
More to the point, it’s together with proprietary data that these sources make our understanding of a business’s market position truly whole – by revealing what all audiences are saying and wanting (or not). Those signals are as valuable as existing customers’ inputs or feedback.And so, whilst I agree learnings from customer data are essential for businesses to prosper, they are only focusing on one part of the whole picture. Mining data signals outside of your own backyard is as business-critical to achieve and maintain growth. As Hulu co-founder and former CEO, Jason Kilar, nicely put it, “Our brand is what people say about us when we’re not in the room”.
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Val Morgan is working with Karen Nelson-Field’s team at Amplified Intelligence to study the effect of attention metrics on cinema audiences. As James Bond’s latest film storms the global box office, it’s time for more meaningful metrics – and cinema is in a class of its own on the attention scale, Val Morgan’s Guy Burbidge writes.
The advertising industry deserves a collective round of applause. In the face of a global pandemic, near constant – and ongoing – privacy questions and scrutiny, advertisers innovated and experimented like never before, and the whole market is better for it. Success in the next (hopefully disruption-free) year will require collaboration and partnerships.