Technology Doesn't Replace Talent: Part 2
In the third of three major public announcements in as many weeks, Satya Nadella said on Tuesday that Microsoft plan to play a ‘central role’ in gathering, storing, processing and presenting data.
He wants businesses to have a ‘data culture’ which would mean that every single employee would be able to ask the questions they wanted, and get the answers they needed from the right technology.
Nadella also said that data is the ‘business currency of the future’ and gave details on three new Microsoft services:
- SQL Server 2014 – new in-memory technology which means it can comb through vast amounts of data extremely quickly
- Microsoft Azure Intelligent Systems Service – a cloud service which senses and controls objects connected to the ‘Internet of Things’ (i.e, when all objects become smart and have an internet connection)
- Analytics Platform Service (APS) – combines Microsoft’s SQL Server database with data from Hadoop, to create high performance data warehousing (or ‘big data in a box’ according to Nadella)
According to Microsoft, these new products could help customers capture more than $1 trillion in new revenue and improved efficiency over the next four years.
In a blog following his announcement, Nadella said: “We believe that with the right tools, insights can come from anyone, anywhere, at any time. When that happens, organisations develop what we describe as a ‘data culture’.
Sounds pretty good – essentially you’re empowering your people by facilitating their decision making, based on data driven information.
The thing is though, technology and tools alone are not enough to create a true ‘data culture’.
In the first part of ‘Technology Doesn’t Replace Talent’, I argued that you can have the greatest dashboard in the world, telling you all sorts of wonderful numbers, but if you don’t have the experience or skills to be able to interpret that data correctly, it won’t tell you anything. Or worse, it will tell you the wrong thing entirely, but you won’t know that.
I used the dashboard in my car as an analogy – there’s a setting that tells me what gear I should be in to be at my most economical whilst driving…but it can’t tell me there’s a hill coming up.
So I’ll override the dashboard in that instance, so that I’m in the right gear as I get to said hill. Because I know when the technology’s telling me something wrong.
If every single person has access to data analytics tools, that’s all well and good. But knowing what you’re looking for, what questions to ask, and understanding what the data represents, isn’t something that technology can do alone. It takes personal interference, experience and skill to be able to do this.
Nadella went on to say, “In the past, only people who knew how to use a complicated database could ask questions, do analysis and learn things. The next generation of technologies will be about the apps that will let anyone, regardless of technical skill, sift through large quantities of information and discover new things…”
Again, technology alone, no matter how much simpler it will make the process of analysing large amounts of data, is only half the story. Asking the right questions, and knowing the impact of the answers, is absolutely fundamental.
Just as crowdsourcing uses the process of gathering loads of ideas or content, interpreting data is the same. The data might come back and tell you something consistent, but still might not give you the right answer. Just as Henry Ford once said, “If I had asked people what they wanted, they would have said faster horses.”
Imagine if he had used crowdsourcing…Had Ford been a different type of person and listened to his “data”, would we have seen aerodynamic horse hooves before we saw the establishment of the Ford Motor Company?
Let’s take a look at the dashboard proving extremely useful, taking Netflix as an example….but even this has a twist in the tale and goes to show the importance of gut feeling.Netflix uses analytics and big data on a massive scale, and being internet based, they have the ability to get to know their customers really well. Netflix can see when we abandon TV shows, what time we watch them, when we rewind or fast forward, and our browsing behaviour.
It analyses this information to create a richer viewing experience, data which traditional television simply doesn’t have access to. Their viewing figures are only approximate, and based on a sample in any case.
This article provides a great overview on the level of science Netflix applies to its viewing choices, and the methods they use to get people to use their subscription as much as possible, and therefore limit the amount of cancellations (such as enabling automatic play for the next episode in a series).
Netflix also applied data analytics to making the decision to produce House of Cards, their first original production. House of Cards has been very successful and well-reviewed; in fact a survey showed people are 86% less likely to cancel their subscription based on that show alone.
But, as the article mentions, data would probably have told you that making ‘Breaking Bad’ was a terrible idea. It was a drama and they’re unpredictable in ratings, would star an actor (Bryan Cranston) only really known for his comedic roles, and it was written by someone who used to work on the X Files.
And yet by the series finale you have Anthony Hopkins proclaiming in a wonderful fan letter to Cranston, “That kind of work/artistry is rare, and when, once in a while, it occurs, as in this epic work, it restores confidence.” Clearly, there are times when we should ignore the data, and go with our instincts.
I’m not saying that data analytics is a bad thing – in fact quite the opposite is true. How we use data now is what will help us get closer to our customers, and give us a truly competitive advantage.
Empowering your people to make decisions which are based on statistical information is only to be encouraged. You might just find that one Henry Ford character among your staff who pipes up and says, “Actually, I think we should consider this…” and you’ll discover something brilliant.
However, control is important. Dashboards and data don’t always tell the whole story, and sometimes it can get things wrong completely. Interpreting data is a skill that can’t be replicated simply because there are some great tools available.
To create a true data culture, technology must work hand in hand with intelligent human insight.