Paul Wallbank – Brilliant Communications

Tag: big data

Seeing the full picture
Being able to make sense of data is one of the challenges of modern business.

In the case of data visualization service Encompass, the business was founded after its founders were caught out by not knowing all the information behind business deal.

The latest Decoding The New Economy video is an interview with Roger Carson and Wayne Johnson, the co-founders of Encompass, a cloud based data visualisation company.

Encompass takes corporate information such as credit information and business registration details and renders it into a form that’s easy to read for salespeople, bankers or anyone doing due diligence on an organisation or individual.

“A lot of it is about bringing the information together and making it usuable and simple to use,” says Wayne. “If you can’t get that information easily and it takes relationships with lawyers to put it all together or your own legal advisor takes a long time to get this together, it’s costly and you may miss things.

Wayne and Roger’s path to starting Encompass came from being caught out in a property deal where it turned out some of the business partners wouldn’t have passed close examination.

“The property venture we went into was not a success,” Roger explains. “If we had known about the people and the properties and the companies involved on the other side of that transaction we probably would not have got involved in it.

“The genesis of this product really came about because we were involved in a transaction where we didn’t have the full picture, we couldn’t get the full information quickly and we therefore realised there had to be a better way for people to look at commercial transactions and get the full picture.”

It’s often said that information is power, but the real power lies in being able to understand the data we’re being flooded with. Encompass are a good example of the new breed of business that’s helping others deal with the masses of information we’re all being inundated with.

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February 10, 2014
Uber and the evolving business model
Last year we looked at Uber and speculated the software that runs the business positions the company to be more than just a hire car booking service with applications in logistics and other sectors.

This week Uber’s CEO Travis Kalanick is getting plenty of coverage in the media with extensive profiles in both the Wall Street Journal and Wired.

Wired’s profile of Kalanick and Google raises Uber’s potential in logistics, funded by a $258 million fund raising led by Google Ventures last August.

“We feel like we’re still realizing what the potential is,” he says. “We don’t know yet where that stops.”

While Wired speculates about how Uber would perform against Amazon and Walmart, the car service is different in being more of a big data play than its established, possible competitors.

The three businesses would be very different creatures in the way they would address consumer markets, it may even be that Uber is more suited to being a B2B or wholesale operation rather than a retailer like Walmart.

Interestingly Kalanick looks at a target of 2,000 staff by the end of this year reports in his Wall Street Journal interview.

Mr. Kalanick: We have 550 employees. That’s approximate. We’re definitely going to be well over 1,000, maybe in the 1,500 to 2,000 range [by the end of 2014].

Having a staff target so high is interesting, it certainly indicates Kalanick sees plenty of growth ahead in the business.

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January 8, 2014
Connecting the vending machine
Wired Magazine’s Klint Finlay speculates why Coca-Cole would want sixteen million MAC address for their vending machines.

That Coca-Cola has connected all their vending machines shouldn’t come as a surprise, probably the only thing moderately unusual from this story is that the soft drink company organises its own hardware rather than getting the machine manufacturers to do it.

Vending machines being connected isn’t new, back in the days of dial up modems some of the more advanced one would use phone lines for basic diagnostics.

Today most vending machines have a cellular connection used for payments, stock monitoring, fault warnings and vandalism detection.

A visit to my local swimming pool today showed this, the Coca-Cola branded machine machine outside the change rooms offers credit payments and in the not too distant future will probably include some sort of NFC type option.

On top of the the machine is a little aerial for the back to base communications. So the device can validate and bill cards, report back when stock levels are low and alert operators to anything untowards happening.

A big opportunity for the soft drink companies and their distributors is analysing the information about buying patterns at various locations — it’s a classic Big Data play.

So it’s not surprising Coca-Cola has registered a block of MAC addresses as the company will probably need several more 16 million blocks in the not too distant future as more of their operations from bottling plants to vending machines require unique connections.

Vending machines are a small but obvious example of how the internet of things is evolving, in the near future most consumer devices will have similar options.

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January 5, 2014
King Canute and Google: When the algorithm is wrong
As society and business drown in big data we’re relying on algorithms and computer programs to helps us wade through a flood of information, could that reliance be a weakness?

British Archeology site Digital Digging discusses how Google displays Manchester United winger Ryan Giggs in the results search for Cnut, the ancient king of Denmark better known in the English speaking world as King Canute.

Apparently Giggs appears in the search results for Canute because of the footballer’s futile attempt to hold back a tide of information about his love life.

While Google’s algorithm seems to have made a mistake, it’s only doing what it’s been programmed to do. A lot of trusted websites have used the term ‘Canute’ or ‘Cnut’ in relation to Giggs so the machine presents his picture as being relevant to the search.

Confusing Ryan Giggs and King Canute is mildly amusing until we consider how critical algorithms like Google Search have become to decision making, there are no shortage of stories about people being wrongly billed, detained or even gaoled on the basis of bad information from computers.

The stakes in making mistakes based on bad information are being raised all the time as processes become more automated, a chilling technology roadmap for the US military in Vice Magazine describes the future of ‘autonomous warfare’.

By the end 2021, just eight years away, the Pentagon sees “autonomous missions worldwide” as being one of their objectives.

Autonomous missions means local commanders and drones being able to make decisions to kill people or attack communities based on the what their computers tell them. The consequences of a bad result from a computer algorithm suddenly become very stark indeed.

While most decisions based on algorithms may not have the life or death consequences that a computer ordered drone strike on a family picnic might have, mistakes could cost businesses money and individuals much inconvenience.

So it’s worthwhile considering how we build the cultural and technological checks and balances into how we use big data and the algorithms necessary to analyze it so that we minimise mistakes.

Contrary to legend, King Canute didn’t try to order the tide not to come in. He was trying to demonstrate to obsequious court that he was fallible and a subject to the laws of nature and god as any other man.

Like the court of King Canute, we should be aware of the foibles and weaknesses of the technologies that increasingly guides us. The computer isn’t always right.

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December 31, 2013
Big Data, retail and the 80/20 rule
Sorting out troublesome customers is one of the major benefits that big data offers businesses, a profitable example lies in reducing returns to online stores.

One of the banes of online retail is dealing with returns, the industry pioneers overcame objections to shopping over the web through no-questions-asked returns policies that’s trained customers into expecting they can send items back regardless of the reason.

The Frankfurt School of Finance and Management’s Christian Schulze surveyed nearly six million internet transactions and found returns are effectively costing online retailers half their profits, as The Economist reports.

Leaving that sort of money on the table is painful for any business and online retailers are trying to find ways to reduce those return costs by sacking their customers;

But this risks a backlash: rejected shoppers are likely to rush to the newspapers or social media to complain—and their gripes may turn other, more profitable customers against the firm.

Much of this comes down to Pareto’s Law, that 80% of your problems will come from just 20% of customers, and a key imperative in business is to get the troublesome, high maintenance customers buying from your competitors without being too obvious.

Identifying those troublesome customers is where Big Data comes into play, coupled with intelligent analytic tools businesses are able to identify who is more likely to return a product or dispute a bill before the sale is made.

As the Wall Street Journal reports many online retailers are exploring ways they can reduce the return rates using Big Data and analytics.

By giving buyers access to their purchasing history stores are able to suggest when a customer is buying something that isn’t appropriate or the wrong size.

The WSJ cites fashion retailer Rue La La, which lost $5 million in returns last year, as an example.

For instance, a customer who has continuously bought the same brand of dress shirts in both a small and a medium might see a note pop up saying: “Are you sure you want to order the small? The last five times you ordered both sizes, you only kept the medium,” Chief Executive Steve Davis said.

Another tactic for retailers is to discourage frequent returners from buying high margin goods through targeted vouchers and offers. One point the WSJ article makes is how differential pricing is going to be applied – if you regularly return goods then expect not to be offered the best discounts when you visit the retailer’s website.

Many returns though are the result of genuinely dissatisfied clients and this is where improving customer service kicks in, the WSJ describes how some retailers are now providing video tutorials for their products and increasingly smarter customer service can be used to avoid returns.

With the increased sophistication of customer analytics and support tools, we’ll see online retailers squeeze more profit out of their businesses as well as look after their most profitable clients.

The problem for ‘bricks and mortar’ retailers not deploying new technologies is they won’t have the tools to compete with their savvier online rivals.

A good example of legacy managers struggling in the face of chronic under investment are Australian retailers and this week the Myer department store chain had to shut down its online outlet after the system collapsed.

There is no timeline on when Myer’s website will be back up. It’s a tough time for those retailers that haven’t invested in modern system and an even tougher time for companies with legacy managers like those at Myers.

The use of big data in analysing shopping behaviours is one area where well managed retailers will out perform their poorer rivals, it’s hard to see how companies like Myer will survive in the modern era of business.

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December 28, 2013