5 Business Success Factors (So You’re Ready for Anything!)

We are sweltering in the Northern Hemisphere with record temperatures, so here’s a “cool” idea on how businesses can get ready for anything by applying these success factors.

Every winter, the media is full of stories of record snowfalls somewhere in the world, whether in the US, Europe or in the Far East. Despite all the sophisticated technologies at our disposition, we just never seem to be prepared. So what are the success factors of readiness?

Remember winter storm Juno in the USA in 2015? It dropped a couple of feet of snow on the Eastern coastline of North America. According to the Weather Channel its snowfall broke records in Worcester, MA, although in most other places it fell far below that of other storms from 2013 all the way back to 1978.

In the same year, in the North of the UK, the region was battered with a rare blast of thundersnow – an unnerving combination of thunderstorms and downpours of snow. As if that wasn’t enough, they were soon preparing to do battle with the elements with yet another storm shortly afterwards.

Now what do all these storms have to do with business you might wonder? Well for me they are a great illustration of the problems that many companies can face from time to time. Governments and city maintenance teams prepare for winter by organising vast stocks of grit and salt, as well as heavy snow-clearing machinery. But despite all this preparation, they still seem to be caught off-guard when they need to use them.

The same goes for businesses. Companies follow trends and expect to be ready for anything; they’re not!

The reason is that there are two serious problems with that way of thinking:

Firstly they are all following the same trends, attending the same trend “shows” & conferences, and getting the same or at least very similar trend reports.

And secondly, they think that knowing the trends will somehow protect them from future risks and catastrophes. However, having the right material still doesn’t stop bad things happening, as we’ve seen this winter. 

So let’s take a look at what you can do to be better prepared and not get regularly “snowed-in” as many countries are this winter.

The Problem with Trend following alone

As I already mentioned, trend following suppliers are providing almost identical information to all their clients. This results in their clients then working on the same ideas & concepts and eventually launching very similar, non-competitive products and services. Have you never wondered why suddenly everyone is talking about a certain topic, or using similar slogans in their advertising? Simplistic trend following is probably the reason. 

As an example, think about how many companies have used the idea of “YES” and “NO” in their advertising in the past couple of years. These include:

  • The Swiss Migros Bank: see the videos here – sorry only in French & German but still easy to understand
  • BMW 320i YES, YOU, CAN
  • Orange telecom mobile
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Market Research & Insight’s New Role is Customer Centricity Champion

I’ve just returned from a trip to Belgium. Apart from the greater presence of armed military personnel, it was business as usual. On Tuesday, I presented at BAQMaR, the Belgian very innovative and forward-thinking research community. What a fantastic and inspiring experience!

My talk was on how market research and insight teams could further progress the industry and their careers, by becoming the customer’s voice within their organizations. Here are my three Big Ideas and three New Skills that will enable market research to make a bigger and more valuable impact on business.

Big Data is not the star of the show, it’s just the support act

Everyone seems to be speaking about big data these days. Not a day goes by without an article, podcast or post about the importance of big data. I don’t dispute the new opportunities that information from smart chips, wearables and the IoT provides. However, data remains just a support to business and decision making. It’s what you do with all the data, how it is analyzed and used, that will make a difference compared to past data analysis.

Business doesn’t get what it needs

One of the problems that has been highlighted by BusinessIntelligence.com is that business leaders and especially marketing don’t get what they need. Executives still struggle with email and Excel spreadsheets whereas what they want are dashboards. They want someone to have thought about their needs and to provide them with the information they need, in a format that is easy to scan, easy to review and easy to action. They also want mobile access, so they can see the I formation they want, where and when they need it.

Information must become smarter

The current data overload means marketing are overwhelmed by the availability of data, especially from social media. They need help in organizing and making sense of it all. My suggestion is to use it to better underst and the customer. The who, what, where and above all why of their attitudes and behavior. This will certainly enable them to start targeting with more than the demographics that a frighteningly high number are still using to segment, according to AdWeek.

Information needs to become useful

While big data can have many uses, it is often so complex and unstructured that many businesses are unable to make it useful for business decision-making. My suggestion would be to start by asking the right questions of it. Data, both big and small, is only as useful as the questions we ask of it. (>>Tweet this<<) If we ask the wrong question we can’t get the answers we need. Therefore start by considering what attitudes or behaviors you want to change in your customers. By bringing the customer into the beginning and not just the end of the analytical process, we will make better use of the information available to us.

Market research and insight teams need new skills

In order to satisfy and leverage the opportunity that … Click to continue reading

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
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Try a New Perspective on Business Intelligence: How to get More Impact & Answers

Last week I presented at the first Swiss Business Intelligence Day. It was an inspiring conference to attend, with world-class keynote speakers opening the day. They included Professor Stephane Garelli from IMD, Philippe Nieuwbourg from Decideo  and Hans Hultgren from Genesee Academy.

After such an illustrious start, you can imagine that I was more than a little nervous to present my very non-IT perspective of business intelligence. However, the presentation did seem to go down well, so I want to share with you some of the ideas I talked about. Not surprisingly, with my passion for customer centricity and always with the end-user in mind, I took quite a different perspective from that of the majority of IT experts who were present.

BI should Collaborate More

With the explosion of data sources and the continuous flow of information into a company, managing data will become a priority for everyone.

The Big Data market, which more than doubled last two years, is forecast to triple in the next four, according to Statista. BI will have to exp and its perspective, work with more varied sources of information and exp and its client base.

In the past BI was inward looking. It ran data-mining exercises, reviewed corporate performance, developed reports and occasionally dashboards. It was, and still is in many organisations, mostly concerned with operational efficiencies, cost-cutting and benchmarking.

The above plot is my own, simplified view of how BI fits into data management within most organisations today. The other three quadrants are:

  • Competitive intelligence (CI) uses external competitor knowledge to support internal decision-making. Although BI is sometimes considered to be synonymous with CI because they both support decision-making, there are differences. BI uses technologies, processes, and applications to analyze mostly internal, structured data. CI gathers, analyzes and disseminates information with a topical focus on company competitors.
  • Investor Relations (IR) uses internal data to get external people, such as shareholders, the media or the government, to support and protect the company and its views.
  • Market Research (MR) on the other h and is mostly outward looking. It studies customers’ behaviours & attitudes, measures images & satisfaction, and tries to underst and feelings & opinions. That information is then used, primarily by marketing, to develop actions and communications for these same customers.

The four quadrants, even today, usually work in isolation, but that will have to change with this new data-rich environment in which we are working.

BI is Ripe for Change

 

According to a recent (Jan 2014) Forbes article, BI is at a tipping point. It will need to work in new ways because:

  • it will be using both structured and unstructured data
  • there will be a consolidation of suppliers
  • the internet of things will send more and more information between both products and companies.
  • thanks to technology, data scientists will spend more time on information management & less time on data preparation. At present it is estimated that they spend 80% of their time on data
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