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You’ve Got Data? Well Don’t Start There!

Did the title about data make you curious? Great!

Of course, in today’s data-rich environment I’m not really suggesting that you actually ignore it! However, in working with clients around the world and in numerous industries, I have found that many are lost by the wealth of information that is available to them. In fact it seems to drown out their reasoning of what to do and they remain frozen in indecision. Is this your case? If so, then just follow the steps I detail below and you will soon be doubling, quadrupling, if not 10x the ROI of your data.

 

The Current Situation with Data

Data is everywhere and most organisations are drowning in it! Technology is being blamed for disrupting businesses, but most have simply not adapted to this new data-rich world.

I admit, a lot has changed. Consumers are adapting their behaviours to the trading of their personal information. Companies are changing business models as their value shifts from products to services, or even to the sale of the information they gather.

Some organisations are reinventing themselves to take advantage of these changes. Others are ignoring them – at their peril, since they are risking to become the next Kodak, Borders or Blockbusters. If you’re interested in reading more about the US Retail Apocalypse and the 23 big retailers closing stores then I highly recommend this post on Fox Business.

So what should you do, whether you are in manufacturing or retail? Well, I believe that you should start by renovating your business model to take advantage of the countless new opportunities open to you. And in my opinion, you had better do it sooner rather than later, because your competition almost certainly will!

 

The Opportunity

Yes you have data and information, but if you’re a regular reader of my blog, you will know that you have to turn these into knowledge and understanding, and then into actionable insights. And this can only be done by asking the right questions of your data and information.

If you are struggling to take needed action despite a wealth of information, then this is certainly where you should start making changes – fast!

A 2015 Capgemini and EMC study called “Big & Fast Data: The rise of Insight-Driven Business” showed that:

  • 56% of the 1,000 senior decision makers surveyed claim that their investment in big data over the next three years will exceed past investment in information management.
  • 65% admit they risk becoming irrelevant and uncompetitive if they do not leverage data. This is especially true given that non-traditional providers, like startups thriving on big data processing, are moving into their industries.
  • Although companies realize they desperately need to dig into data analytics to maintain their business position, 45% surveyed think their current internal IT development cycles are not sufficient for new analytics and don’t fulfill their business requirements.
  • Making matters worse, over half (52%) of those surveyed see the speed of their organization’s insight generation from data analytics as constrained by its existing IT infrastructure.

So what has happened in the past couple of years? Not a lot in terms of usage, but a lot in terms of data gathering; just check out the graph below from Kleiner Perkins for current and estimated growth of data volume.

 

Big data trends Kleiner Perkins 2017

Of course big data has been big news for years, thanks to its 5Vs (volume, velocity, variety, variability, value). These were the driving forces behind the need and finally the computing upgrades which made it possible to adopt a new way of analysing it all.

This article by Olivia Ryan sums up the “6 ways big data expansion can significantly damage our privacy.” These are the major points which the GDPR is hoping to address, and about time too in my opinion.

Today it’s the EU’s GDPR or General Data Protection Regulation, with its stricter rules coming into play later this year, which has everyone concerned. It is definitely worth checking out the details here if you are not sure what you need to change by when.

Interestingly, there is no equivalent federal law in the US (for now), but that doesn’t mean you can ignore it if your business is based there. Find out more in this excellent article on Forbes.

It’s true that companies do recognise all the threats detailed in the earlier mentioned study, and while startups flourish in every industry, the mastodons of commerce are slow to change, hence the need for GDPR. (see below for an alternative approach to individualised data utilisation)

 

An Alternative Approach

Data comes into its own when used for personalised engagements. However, there is an alternative or complementary approach that some organisations are now using. This is to address global issues such as resource management, water usage or pollution, which certain customers feel passionately about.

One example is Nestle whose relatively new CEO Mark Schneider is finally bringing some fresh air to the dark and dusty halls of their Vevey offices. However, cutting costs, selling less attractive business units (such as US candy to Ferrero) to upgrade their image will not bring sufficient change that consumers demand of large corporations today.

Compare this to the efforts Unilever’s CEO Paul Polman, who has made his organisation one to be admired by consumers and shareholders alike. As they say in their website

“We aim to use our scale and influence to help bring about transformational change in four key areas where we believe we can make the biggest difference:

  • Taking action on climate change and halting deforestation
  • Improving livelihoods and creating more opportunities for women
  • Improving health and well-being
  • Championing sustainable agriculture and food security.”
Bold words indeed! And they can only do it with the help of data and metrics to measure and follow their progress. Given these very different approaches to preparing for the future, I know which one I am betting on – and you? Let me know in the comments.
The appeal of this alternative approach is confirmed by the results of SalesForce’s recent research findings reported in the “State of the Connected Consumer.” To summarise their six conclusions:

  1. Information-Savvy Customers Now Control the Marketplace. 70% of consumers agree technology has made it easier than ever to take their business elsewhere.
  2. The Culture of Immediacy Drives Mobile-First Expectations. 64% of consumers expect companies to respond and interact with them in real time.
  3. Customers Still Value Human Connections in a Tech-Driven World. Two-thirds of consumers say they’re likely to switch brands if they’re treated like a number instead of an individual.
  4. New Data-Sharing Attitudes Spark Next Era of Marketing Personalization. 63% of millennial consumers agree they’re
    willing to share data with companies that send personalized offers and discounts.
  5. Smarter Use of Customer Information Expands Opportunities for Sales.More than three-quarters of consumers say it’s absolutely critical or very important to work with a salesperson who is focused on achieving customer needs instead of making a quick sale.
  6. Fast, Personal Service Is Directly Linked to Customer Loyalty. 71% of consumers say that customer service provided on any day at any time has an influence on loyalty, and almost as many (69%) say the same about personalized customer care. 

Looking at these findings, it gives me hope for a more human approach to customer connections by manufacturers and retailers alike. I believe that those which fail to take this informed customer into account is unlikely to survive the next decade.

 

Making Data Analysis the Beginning and Not the End

I mentioned above and also dedicated a whole post to the topic of technology being an enabler not a disruptor of businesses. (Check out “Technology is the Enabler not the Disruptor (So Stop Using it as an Excuse)” for more on this) Many organisations think that their problems with data will end when they get the latest technology platform installed or start using the newest system for analysing it. Nothing could be further from the truth. Technology enables improved analysis perhaps, but as previously mentioned, data is only as good as the questions you ask of it. That’s why data is the beginning of your business solution, not the end.

Data is only as good as the questions you ask of it. #BigData #Analysis #Information #CEX Click To Tweet

In addition, in “The Impact Of Changing Consumer Expectations On Manufacturers” Steve Smith spells out the situation very clearly for manufacturers:

“With new consumer expectations being set by companies that disrupted their respective markets — Uber, Amazon, Netflix — the previously accepted levels of customer service are no longer good enough.”

What these three companies demonstrate perfectly is that technology has merely enabled the consumer to get more of what they want, whether that is travel, retail or entertainment. Although these are three very different industries, they have attracted a growing number of customers because what they offer is a trustworthy service. No, rather they offer few surprises, and when there is disillusion, they sort it out quickly, and usually far above and beyond the customers’ expectations. Surprise and delight are the table stakes of today’s world of customer service.

Surprise and delight are the table stakes of today's world of customer service. #CEX #CRM #CustomerSatisfaction Click To Tweet

In Conclusion

Coming back to the title of this post, as you can see there is a lot to do before analysing all the data you have. And probably it’s a lot more than you even know about at present, at least from my experience!

You can’t go wrong if you start with the customer and identify what you need to know and understand in order to go beyond their expectations.

You can't go wrong if you start with the customer & identify what you need to know & understand. #CEX #CRM #Customer Click To Tweet

Make a list of all the things you want to know and then see if you have the information to answer them. In many cases you do, it just hasn’t been analysed in a way that makes the solution obvious. That’s when you should review and eventually update your platform and systems.

Doing this any earlier will be like buying a fancy new hammer to crack a nut! What you need to understand is the best way to crack the nut; often times the hammer is fine for cracking if you use it correctly.

If you’re drowning in data and thirsting for insights then we should talk. Book a free advisory session and I’ll give you some ideas on how to crack your own nut!

 

 

 

Market Research, Business Intelligence & Big Data: Have we Forgotten about Human Data?

The annual pilgrimage to the ESOMAR Conference took place last week in Dublin. I heard that there was much discussion, both on and off the stage, about Big Data and the future of market research. Hopefully, the whole profession will get behind one initiative, instead of each individually trying to “solve world peace” on their own!

This week sees the second Swiss BI-Day taking place in Geneva and there will no doubt be similar discussions about Big Data and the future of Business Intelligence.

It appears that Big Data is not just a buzzword or a commodity that has been likened to oil; it has become the centre of a power struggle between different industries. Many professionals seem to be vying for the right to call themselves “THE Big Data experts”.

This got me thinking about the future of data analysis in general and the business usage of Big Data more specifically. There seems to be no stopping the inflow of information into organisations these days, whether gathered through market research, which is proportionally becoming smaller by the day, or from the smartphones, wearables and RFID chips, that get added to every conceivable article, more generally referred to as the IoT (Internet of Things). Who will, and how are we to better manage it all? That is the question that needs answering – soon! (>>Tweet this<<)

Data Science Central published an interesting article earlier this year called “The Awesome Ways Big Data Is Used Today To Change Our World”. Already being a few months old probably makes it a little out-of-date, in this fast changing world we live in, but I think it still makes fascinating reading. It summarises ten ways that data is being used:

  1. Underst anding and Targeting Customers
  2. Underst anding and Optimizing Business Processes
  3. Personal Quantification and Performance Optimization
  4. Improving Healthcare and Public Health
  5. Improving Sports Performance
  6. Improving Science and Research
  7. Optimizing Machine and Device Performance
  8. Improving Security and Law Enforcement
  9. Improving and Optimizing Cities and Countries
  10. Financial Trading

Many of these are not new in terms of data usage nor business analysis. What is new, is that the data analysis is mostly becoming automated and in real-time. In addition, the first and second items, which were largely the domains of market research and business intelligence, are now moving more into the h ands of IT and the data scientists. Is this a good or bad thing?

Another article posted on Data Informed a few months after the above one, talks about The 5 Scariest Ways Big Data is Used Today   and succinctly summarises some of the dynamic uses of data today. The author of both pieces, Bernard Marr, wrote that “This isn’t all the stuff of science fiction or futurism. Because the technology for big data is advancing so rapidly, rules, regulations, and best practices can’t keep up.” He gives five examples of where data analysis raises certain ethical questions:

  1. Predictive policing. In February 2014, the Chicago Police Department sent uniformed officers to make “ custom notification visits to individuals whom they had identified, using a computer generated list, as likely to commit a crime in the future. Just one step towards the “Minority Report”?
  2. Hiring algorithms. Companies are using computerized learning systems to filter and hire job applicants. For example, some of these algorithms have found that, statistically, people with shorter commutes are more likely to stay in a job longer, so the application asks, “How long is your commute?” Statistically, these considerations may be accurate, but are they fair?
  3. Marketers target vulnerable individuals. Data brokers have begun selling reports that specifically highlight and target financially vulnerable individuals. For example, a data broker might provide a report on retirees with little or no savings to a company providing reverse mortgages, high-cost loans, or other financially risky products. Would we want our own families targeted in this way?
  4. Driving analysis devices may put you in the wrong insurance category. Since 2011, car insurance companies like Progressive and Axa, have offered a small device you can install in your car to analyze your driving habits and hopefully get you a better rate. But some of the criteria for these lower rates are inherently discriminatory. For example, insurance companies like drivers who stay off the roads late at night and don’t spend much time in their cars, but poorer people are more likely to work the late shift and to have longer commutes to work — both of which would be strikes against them when it comes to calculating their auto insurance rates.
  5. Walmart and Target determine your life insurance rates. OK, not directly, but Deloitte has developed an algorithm, based on “non-traditional third-party sources” that can predict your life expectancy from your buying habits. They claim that they can accurately predict if people have any one of 17 diseases, including diabetes, tobacco-related cancer, cardiovascular disease, and depression, by analyzing their buying habits.

Marr starts this article by very briefly discussing privacy and inherent biases in data. I think these issues are far more urgent than deciding whether it is market research, business intelligence or data scientists that are in charge of the actual data analysis. Perhaps we all need to work together so that the “Human” side of data is not forgotten? After all, most data comes from people, is understood – if no longer strictly analysed – by people, for the benefit of people, to help change people’s behaviour. What do you think? Join the conversation and let your voice be heard. (I’ll be presenting this very topic at the Swiss BI-Day this coming Tuesday, so I do hope that you will pop by and listen)

Winning Customer Centricity BookThis post includes concepts and images from Denyse’s book  Winning Customer Centricity. You can buy it in Hardback, Paperback or EBook format in the members area, where you will also find downloadable templates and usually a discount code too.

The book is also available on Amazon, Barnes and Noble, iBook and in all good bookstores. If you prefer an Audiobook version, or even integrated with Kindle using Amazon’s new Whispersync service, it’s coming soon!

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