Guest Post from Seeker on Big Data

One of our startups, Seeker, were invited to an Ogilvy Lab Day yesterday, where the entire event was focused on Big Data. Tielman de Villiers, the co-founder and CTO at Seeker Industries, went along to find out just how big the debate is around big data. He was particularly keen to hear opinions surrounding just who owns all of this data, is it possible data can become too “clever” for its own good, and is there really that much value in “big” data? Here is his report, for those of us who missed the event.

Photo by @nicoleyershon

"There are currently many unanswered questions concerning the creation of big data, it's ownership, and it's accuracy.  Let's go through some of the issues discussed at the Lab Day.

Matt Bayfield, head of data practice at OgilvyOne Worldwide, asked what is the role of advertising, if brands start knowing everything there is to know about you? It’s not only the ownership of the underlying data, but also of the data on top the data, as Dr Trevor Davis, consumer products expert at IBM, mentioned.  For example, if you start making predictions using Facebook’s Opengraph or Google Trends, where does the legal responsibility start and end?

And what if all that personal data is actually a bit of a lie? So, even if Google, Facebook and Amazon captures, processes, segments, and targets everything users are willing to share, how “truthful” and representative is it really? Liri Andersson, co-founder of This Fluid World, spoke of examples where the “real” data is still outside of the “system”. For example, product recommendations often occur in forum-based discussions, which influence our decisions about purchases. In other words, how useful is the big data really with regards to predicting future behaviour?

Then there’s the slightly “scary” part of big data, when data analysis algorithms become so complex and relied upon by corporations that plain old human common sense goes out the back door. Stan Stalnaker, founder director of Hub Culture and the brains behind the Ven currency, warned of becoming too reliant on machine driven algorithms. Just look at what is happening in the world of corporate finance with programs driving and controlling sales in financial markets. What happens when this happens in the world of digital marketing, with the most personal of our personal data?

Big data also seems to be big grey voids. Spotting the little clusters of data with significance inside the masses of greyness (ie, “sparse” data), and doing it in “slow time” (ie, looking back at long historical trends, as opposed to right here, right now) is something which Dr Davis used to “predict” fashion trends. For those left wandering, it’s steampunk."

Are Product Days Productive?

Sometimes you just need to knuckle down and get some work done. But what's the best way to do this? And what about all the other stuff you need to do before you can even start? Well, yesterday Seeker had a Product Day, and so I decided to catch up with the Founder and CEO, Daniel Wilson, to see how (and whether) it works.

1.       What is a product day ?

A product day is a full day when we step out of our regular roles to understand what we’ve got in the product, where we are as a business, and what we want to do over the next 3-6 months.  It gives us a chance to think about our tech and our customers at a higher level.

2.       Why did you arrange it?

The main point was to stop any silos of purpose and knowledge building up, as we’re all working semi-independently because there aren’t many of us.  We need to all be working on the same plan, or we won’t make the right sort of progress.

3.       What did you want to achieve from it ?

We took an inventory of features built, we planned the next 3 months major features to build (develop, or dev), everyone knows our goals around sales and investment

4.       What methods did you use and which ones work best?

We used lots of brainstorming, and we had bits of cardboard and sticky notes, which allowed us to move our ideas around afterwards into more logical groupings.  We used the important/urgent matrix (which is one of my very favourite things) to prioritise our work.

5.       What did you actually achieve?

A sense of purpose and a to do list.

6.       What's the next step?

Today the tech guys are sizing the dev work and planning iterations, and I’m starting to work on more heavily on our sales website, because we realised it was a major blocker to a lot of other work we wanted to do.

7.       Any advice you'd give to startups now in hindsight?

Do more prep than you were going to (My section on “state of the nation” was harder to talk through off the cuff than I had thought), and expect to go through fewer items in the agenda: This is really the time to have those discussions that normally get glossed over, e.g. what’s more important, a new feature or fixed bugs, or sales collateral.