A Kodak moment is coming for organisations that don’t get Big Data

You’d be forgiven for thinking that the data hype is over.  In 2011, McKinsey & Company published a report called Big data: The next frontier for innovation, competition and productivity which forewarned of Big data taking over the world.

Six years later and does it feel like data has taken over the world? Well, I think it depends on where in the world you are.

Those companies and organisations that were early adopters probably think so. Everywhere you look, data is being exploited by smart startups to disrupt traditional businesses. Except that I’m not sure many people outside of the early adopters think that it’s the exploitation of data that’s doing the disruption.

And this leads to big issues. When CEOs and leaders think that Netflix, Uber, Airbnb are just Apps and not data, it’s easy for those people to think that they need an app to compete. They’re wrong.

Most organisations are sitting on mountains of data (or have the ability to get it) that they’re simply not exploiting because they don’t realise that this is what the sharks are feeding on. They will be eaten up in short time if they don’t start collecting/using it soon.

I was recently at a conference where over one hundred of the finest minds in data, in business and organisations, gathered together to discuss and share their experiences within their own organisations.

 

IMG_8324
Corinium CAO Europe conference

 

The people at the conference were at various stages in their organisation adopting a data-centric business model. The huge theme that came out of it as a blocker to anyone talking about why things weren’t happening or why things did happen was senior stakeholder support.

Unless support for data-centricity (not just data projects) comes from the very top, organisations will struggle to do anything but pay lip service. They are ripe for being gobbled up by younger ‘apps’ who get it. Maybe not today, maybe not tomorrow, but soon.

The big danger here isn’t individual businesses and organisations failing. Plenty of companies have failed to grasp the significance of emerging technologies in the past (Blockbuster, Kodak being the famous ones) and the world hasn’t collapsed.

What’s different here is that when multiple organisations fail in the new world, there’s usually just one or two huge winners who snap up the consumers due to the relative ease and speed they can spread without traditional advertising, building and staff.

This is bad for business, competition and ultimately the consumer, no matter how friendly and do-no-evil the newcomers seem.

The impression that I got from the conference is that everyone, even in large organisations who ‘get it’, are struggling. Linkedin failed to realise the significance of its own data until someone fought for a small ‘people you may know’ section on the homepage that made return visits go through the roof. And Linkedin is an example where they already have the hard work of the data done.

Linkedin failed to realise the significance of its own data until someone fought for a small ‘people you may know’ section on the homepage that made return visits go through the roof. And Linkedin is an example where they already have the hard work of the data done.

And Linkedin is an example where they already have the hard work of the data done. The governance, the skills, the technology were all in place, they just hadn’t productised it. A vast number of incumbents haven’t sorted out the hard bits because they don’t even believe that they need to.

So it was five years since McKinsey wrote that report. Perhaps it was a little early but actually, I don’t think so. We can already see the impact around us if we think of disruptors as being data centric rather than just apps, and incumbents as not.

Just as Kodak thought that the digital camera was about technology rather than photographs.

Kodak is back! (well worth watching the clip below)

 

 

Three right ways and one wrong way to use your data

In my experience, most organisations don’t have a clear plan or structure in place for using the data that they have to its full (or even some) of its potential.

If you find the wrong way of using data below familiar to you, don’t worry, you’ve plenty of company. Acknowledging that you’re making mistakes is the first step on the road to being brilliant, and starting to think about the right ways to use data will put you above 95% of your colleagues.

The wrong way

Picking stats that make you look good/ignoring stats that don’t

Or attribution bias.

I once sent out a chart showing visitors to a website, post-redesign. It looked impressive. A straight arrow indicated that visitors to the site had doubled in the week post-launch. In fact, it looked too impressive and I made it clear in my email to a small group of people to treat it with caution, don’t forward on, and that I’d need to look into it.

I quickly found out that visits to the site were being double counted and the actual rise was more like what I’d modeled. A moderate increase which would grow over the next 3-6 months. I sent out chart number 2.

Here’s the lesson. The first chart was distributed to the whole business even after I’d informed the recipients of the correction. People loved it. The second chart, well, it was awkward when I brought it up in future meetings, was seen by all I thought needed to know and never forwarded on.

Successful data travels far and wide whereas data showing uncomfortable truths doesn’t. Due to the wide variety of data available, it’s possible to make any project look like a success. Visitor numbers low? Show how engaged they were! Awkwardly low retweets? Stick in a single tweet from someone saying how much they loved it! Senior management is rarely data literate enough to question it and so lessons are not learned.

Of course, collecting the data is one thing; accepting what the data tells us is another. We have both worked with all too many organizations where “data-driven decision making” is code for contorting the facts until they reveal whatever senior management expects to see.

-Harvard Business Review, Why organizations don’t learn. Nov 2015

Senior management is rarely data literate enough to question it and so lessons are not learned and the cycle continues. No one likes to see their flaws, it’s uncomfortable but in the areas that we’re forced to learn from mistakes revealed in data in a clear and transparent way, it produces brilliance – think airline pilots, surgeons, the military etc.

Although the above disciplines have been forced into facing up to their data at every level, there’s no reason you shouldn’t do the same even if you may not be dealing with life or death situations.

The right ways to use your data

1. Solve an existing problem

The challenges that an organisation faces are often informed by data and yet people don’t rely on data to solve it (or throw around that one big stat to back up what their biased gut instinct is telling them to do).

A data-literate approach enables better decisions to be made that go against an organisations instincts.

2. Finding a problem/opportunity

Having a team of people within the organisation who can explore data, hiring people who have data skills or training up existing teams at every level can reveal problems and opportunities at all levels. Not all data needs to be big or to result in big decisions being made. Data is probably being used in your organisation badly right now.

Even without knowing that the answers to common insights gleaned from data can be the start of something profound happening within an organisation. Insights such as:

Lots of people search for x

The number of people visiting x is dropping/rising

People in X region do this

People who do X then do Y

3. Education

There is a huge disconnect between the traditional marketing personas that we have in our organisations and actual real behaviour online. Educating people around online behaviours can give a much deeper insight into how people behave and not just how ten people say broadly how they behaved during an interview.

Having employees be able to explore the actual real-life behaviour of the data of an organisation is a powerfully reflective tool and is being used by all kinds of organisations including those that famously rely on gut instinct such as News outlets http://www.digitalnewsreport.org/publications/2016/editorial-analytics-2016/

Of course, it’s not just giving people access to data but encouraging a data-centric approach to working, ensuring people are supported in using that data and encouraging open discussions about the quality and relevance of the data and any insights or assumptions drawn from it. Opening the data up is a good first step though and trusting people to be smart enough to use it wisely is a decision you’ll have to make.

The lessons

1. Face facts – make unbiased data analysis part of your daily routine

2. Solve the problems that data has revealed through exploring that data further

3. Use data to find issues and opportunities

4. Putting data into the hands of people at all levels can be a powerful tool. Trust people to figure it out.

5. Just use it! (but not for the wrong way)