Are your Analytics Investments based on ‘Strong’ or ‘Weak’ Links?

With the recent news that LeBron James is going to make $208M (I have converted to AUD) – and the FIFA World Cup just wrapping up (I can finally sleep again), I have been thinking about a podcast by one of my favourite authors, Malcolm Gladwell – “My Little $100M”.

In the pod, Gladwell makes the argument that if you are trying to make a philanthropic difference by donating money to universities, you are better off donating to smaller, local schools rather than the big brand ivy league schools.  His point is that smaller schools will be more effective because more students will be impacted by that money.

The analogy that Gladwell uses is a comparison between Soccer and Basketball.  In soccer, you are better off improving on the weakest player on the field whereas, in basketball, you are better off improving the strongest player.  As a result, soccer is described as a “Weak Link” sport and basketball a “Strong link” sport.

When we analyse the FIFA 2018 World Cup, the teams with the superstars left in the first round of the knockout stage (Messi with Argentina and Ronaldo with Portugal) but Belgium and France with stars at every position but no real superstars – have lifted the much coveted World Cup.

Alternatively, when we look at the reports about why LeBron went to LA – it was because he wants to win another championship before he retires.  It was clear to him that it was not going to happen at Cleveland. So he went to a franchise that would be able to give him the best chance at achieving that.  LA finished 11th out of 15 teams in the western conference.  Clearly, there is a sense that a single player can make a huge difference in getting a Championship trophy.

So what does this have to do with your investment in analytics?

The key thing to consider when you are looking at an analytics investment is – what type of game are you investing in? A “strong link” game or a “weak link” game.  Strong Link Analytics Investments are analytics projects where there are very few touchpoints with the results of the analytics.  An example is Next Best Purchase on an online store.  This predictive project is designed to provide a recommendation to a store.  So while every customer may see this, from an implementation perspective, it is pretty technical and will require a relatively small team to put the solution into place.  As a result, if you are able to go out to the market and hire the best person in the world at Next Best Purchase (this person probably works for Ali Baba) prediction you significantly increase the likelihood of your project becoming a success.

Weak link analytics investment are for programs of work where an organisation wants to improve their analytics capabilities across many teams or organisational lines.  These are typically considered ‘programs’ rather than ‘projects’.  In most medium to large organisations, there is an ongoing program of analytics projects and improvements that are required to keep up with the evolving digital landscape.  In order for these organisations to keep up with disruptive technologies, they need to build the analytics capability into their DNA.  Doing this will deliver continuous delivery of analytics projects that will make a significant difference to our bottom line.

There is a lot of discussion about data science and data engineering in the press, in contemporary business literature and in business circles.   When we look at the Weak Link vs Strong Link comparison through data, we see that the practice of Data Science is targeted at the idea that a single individual (rock star data scientist) can change your business whereas Data Engineering is about building resilience and scalable analytics capabilities.   Our view is that when organisations focus on building analytics as a capability rather than implementing a “Data Science” strategy, they are prepared to outcompete with their data.

We have built our firm on helping people make better decisions each day using data engineering concepts.  Most of our projects have to do with the repeatable, and scalable aspects of analytics.  Should you wish to learn more about this, reach out to me on LinkedIn. Let’s connect. Let’s catch up for a coffee and discuss how our approach can help your team.

References:

• Link:  Gladwell – My Little Hundred Million   http://revisionisthistory.com/episodes/06-my-little-hundred-million
• Original Research  –  The Numbers Game: Why Everything You Know About Soccer Is Wrong Paperback – July 30, 2013
  by Chris Anderson (Author), David Sally (Author)