How IT Leaders Can Learn From Big Data Industry Changes

IBA Group
Mark Hillary

The Big Data market has transformed how most IT services are bought and sold. Often the customer is a business leader, rather than the CIO, and services are already available, rather than needing to be designed from the ground up.

IT leaders often look at other companies to see what they are doing, it’s usually known as best practice, but what if the entire market is in a state of flux? Some IT companies are now delivering radically different solutions to others. Innovations like the app store concept and cloud based solutions are changing the way that IT services are delivered globally, so how can changes in the Big Data market change how the entire IT industry behaves?

Techrepublic magazine recently outlined some important changes in how IT leaders think about their marketplace. Think of these 5 different changes as examples of what is changing and how it can influence the behaviour of IT leaders:

1.    Off the shelf analytic solutions like Watson from IBM have been customised to be used across many different industry verticals. It’s the same system, but modified for different environments and it can therefore offer immediate results. Everyone is looking for a rapid return on investment today.
2.    Commodity hardware offers a great platform for storage if you are going to keep your data and analytics system internal, rather than in the cloud.
3.    More companies are relying on their suppliers for expertise and innovation today. These are true partnerships now, not just outsourcing arrangements where the cheapest supplier gets the project.
4.    Analytics reporting systems like SAS are still important because they have been tested and developed over so many years, but also because the users are really familiar with the way these systems work. Familiarity is important.
5.    Real time processing systems are changing the way that physical infrastructure is designed and deployed. Look at SAP HANA for an example of how systems using memory in new ways are now feeding back into the design of the physical servers and databases.

What do you think about the lessons from Big Data? Have you seen other ways in which IT is more generally changing because of the way that Big Data is influencing IT strategy? Please leave a comment here.

Big Data Is Becoming Big Marketing

IBA Group
Mark Hillary

It’s fascinating to see how quickly different technologies can move from the world of the technology expert to the mainstream. Think back ten years and it was quite rare to be using the mobile Internet. Some people were struggling along with a very slow connection and an old Nokia handset, but it really wasn’t until the iPhone came out in 2007 that it started becoming easy to use the Internet when on the move.

More recently look at how everyone suddenly understands Augmented Reality (AR) because of the Pokémon Go game. AR has been around for years as a way of overlaying information onto live images, but it has never caught on in a mainstream way until now.

I think we are about to see a similar shift in the way that Big Data is accepted in the enterprise environment too, because it is moving on from just being important to the technologists.

Companies are finding that their customer journey is changing dramatically. This is the route that customers use to find out about products and then buy them. Instead of seeing adverts or marketing materials and then making a purchase, there is a much more complex two-way information flow that can be spread across many channels.

Many organisations are finding that they need to blend all their customer-facing activities together so they can be coordinated. This means that the Public Relations, Advertising, Marketing, Sales, and Customer Service teams all need to be working together because all of them are involved in the customer journey to some degree.

Making sense of all this change requires data and analysis. Smart companies are finding that they can develop better strategies by analysing patterns of customer behaviour, but this requires the analysis of very large data sets. Suddenly Big Data is moving into the world of the marketing team and becoming a valuable tool.

So for any company to succeed in this more complex customer environment, more knowledge about customers is essential and I believe that strong data analysis skills will be needed more than ever. Watch out for this as Big Data skills are going to become a mainstream part of organisational strategy in the very near future.

Enterprise IT Is Changing Fast

IBA Group
Mark Hillary

I saw an interesting Tech Target blog on the storage requirements associated with Big Data projects recently. It’s interesting to see just how many technology concepts are now either blurring together or becoming interdependent.

Consider this as an example. A shipping company installs tracking devices on every vehicle and container they use – it might be tens of thousands of individual items that can now be tracked and monitored and more effectively moved into position. Clearly that increased efficiency is great for the company, but what does it mean in terms of additional IT infrastructure?

First there is a need for an IoT strategy – the Internet of Things – where all these individual items can be tagged and monitored in some way. Either they can independently broadcast their location or they can be monitored using devices that pass in close proximity to them.

So the sheer amount of information that is being captured requires a Big Data strategy because instead of just having an inventory of items, now you need to model the items and their location in real-time. Your database has to become a reflection of the business.

Then a data analysis strategy is required because you need to build models that can maximise the efficiency of the data model and improve on what humans can do manually. As the machines learn the optimum processes, much of the system will be able to run automatically.

But underpinning all of this will be a storage strategy because the amount of data that is created, stored, and manipulated will be huge compared to earlier inventory-based systems. In some cases the data capture will appear to be extraneous – capturing the movement around a port of a single container might not by itself add a lot of value to your business, but when aggregated with the location and movement of every container and analysed, efficiencies can be created.

And this leads back to the use of a cloud strategy to ensure that all these systems always have the storage and computing power available whenever needed.

It’s becoming hard to consider any of these strategies as distinct from each other because the way that IT projects work today has moved far from the world of PC-based applications. Enterprise systems are getting bigger and better, but they need more consideration and strategic planning to succeed.

How Could Big Data Let Us Down?

IBA Group
Mark Hillary

I have often written here about the potential for Big Data to fundamentally change the way that many companies do business. It cuts across industries and is not just a single strategy, it can change the way that existing companies perform and create opportunities for new market entrants.

This cross-industry application of Big Data is where I think there is the most potential for it to become a game-changer. IT experts rarely got to delve so deep into their industry of choice in the past; they focused on the technology and systems that assisted a company.

Now, with Big Data analysis helping doctors to diagnose patients and helping bankers to fight fraud there is a much greater connection between the industrial application of technology and the technology itself. The technology teams need to really understand the business they are working in.

But this is where the peril also can be found. As companies depend more and more on huge data resources and the ability to intelligently analyse this data we are entering a world where data has an enormous value.

Just look at the Panama Papers data leak. A huge amount of secret customer data from the law firm Mossack Fonseca was leaked by a secret source to journalists and it appears to show many wealthy and powerful people using companies in Panama to hide their wealth – and therefore avoid taxes.

Of course, it could be argued that it’s a good thing that this data was leaked. All those powerful people should pay their tax correctly rather than hiding their money, but imagine Facebook was hacked and every online conversation was leaked, or Google and every private gmail message were posted online? Imagine if another law firm were hacked and details of every divorce settlement they have handled were posted openly online?

It’s almost impossible for most customers to now avoid giving out their personal information when dealing with companies and the data is being collected into enormous databases profiling purchases, preferences, and behaviour. Companies in all industries are now wedded to the possibilities presented by the use of this data, but so few are acknowledging that if they ever lost control of the data it could be an existential threat for their business.

Big Data certainly has benefits, but it’s time for companies to acknowledge that with these big data sets come big responsibilities. The companies that fail to protect their customers will not survive.

Big Data and the IoT Are Worth Billions to the UK Economy

IBA Group
Mark Hillary

The Centre for Economics and Business Research (CEBR) recently published new research exploring the size of the Internet of Things (IoT) and Big Data markets in the UK economy with predictions running from 2015 to 2020. These two technologies are expected to add £322 billion to the British economy during this period and although the research is focused only on the UK it can be safely assumed that the effect will be similar in other developed European markets making the effect of these two technologies enormous.

In the UK, the scale of this effect is worth 2.7% of the national GDP and is therefore not just of interest to technology firms, and companies that require technology solutions, these technologies are literally going to change the economy in regions where they are deployed. The opportunities are increasing on a daily basis.

The research indicates that telecoms firms are already strongly adopting both Big Data and IoT solutions, but other industries are catching up and expressing a strong interest in how these technologies can help. Retail banking is expected to overtake telecoms soon for Big Data analytics and it’s no surprise because this is an industry that is being shaken to the core.

The big advantage of improving the use of data analytics is that companies can get to know their customer behaviour better. This means they can adjust their offer to the customer and personalise the service received, all leading to improved revenue and happier customers.

In a business like banking, new start-ups are finding that they can pick a small part of the business, like remittances or lending, and focus on that one service. If they can launch an app offering the service and it is cheaper and better than a traditional bank then they can start growing their market share.

The banks cannot stop this happening, but they can start adjusting their own customer experience so that their existing customers do not desert them for rivals. To make this happen needs information about customer behaviour and that’s where Big Data fits into the story. Knowing your customer needs better insights and technology tools like Big Data analytics and the IoT are what will help you to design how your business is going to work after 2020.

Companies Are Using Big Data Without Realising It

IBA Group
Mark Hillary

Big Data is one of those buzzwords everyone is talking about, but as I have been saying for some time now, most companies are performing some kind of data analysis on their customers or suppliers and have been doing so for years without ever calling it Big Data.

There does come a time when the data being analysed is so huge and fast changing that specific Big Data tools are required, but the reality is that many organisations are already performing some kind of data analysis that could be termed Big Data – without them even realising it.

A new study from Dresdner Advisory Services backs up my observations. When asked specifically if they use Big Data, just 17% of companies responded yes on this survey. 47% said that it might be used in future. However, 59% of the respondents also claimed that Big Data is “critically important” to their business. Something is wrong?

The survey shows that the definition of Big Data is perhaps one of the problems here. Most companies don’t have petabytes of data to analyse and they therefore are performing data analysis, but not thinking of it as Big Data analysis. If the manager doesn’t think of the problem as big enough then they don’t use the term Big Data.

However there are many areas of industry where this is about to change, largely driven by technologies such as mobile and the Internet of Things. Think of an example such as a retailer needing to create the same customer experience for an in-store customer, as that same customer would receive online.

These problems require data. They also need it to be analysed fast. While a customer is in-store and tracked using their mobile device, decisions can be taken about whether to give the customer a discount code based on their profile. During payment, recommendations for other products can be made based on sales history.

All these processes are easy to imagine, some retailers are getting this sophisticated now, but to make it happen it needs the IT system to be joined-up with data that can be analysed in real-time – allowing the system to take decisions itself.

Another easy to imagine examine is with automobiles. Cars are increasingly connected to the Internet via smart phones and wi-fi. They will increasingly diagnose problems and communicate with the manufacturer without the driver being aware that the car is fixing itself. The amount of data captured and exchanged for this to work is enormous, yet in most cases the customer is entirely unaware of the processes taking place.

So how big is big might still be a question for many, but I think that we are on the cusp of an explosion in data use – analysing this much information will certainly be a part of the bigger picture for Big Data.

Trends in Data for 2016

IBA Group
Mark Hillary

One of the trends for 2016 that is certain to only increase in importance is the use of data analysis across many different types of organisation. Big Data and the real-time analysis of data in general is reshaping many industries, redefining how companies build a relationship with their customers.

The fact that this change is applicable across all industries is the most important aspect of this trend. Almost every company in every industry is exploring how a better use of data can give them the edge in 2016. Three specific areas I see as being really important for the year ahead are:

1. The Internet of Things (IoT); tech commentators like talking about the smart fridge that knows you need more eggs, but this is going to be a much more serious trend. If every electric device you own is networked then some incredible new possibilities are created from cars that can self-diagnose and fix problems without you even being aware of it to being able to control anything in your home remotely.

2. Machine Learning; many contact centres have been exploring how robots equipped with product knowledge can handle simple customer service enquiries. As they learn more about what customers want they will get far better and eventually even be able to anticipate what the customer needs. This ability to learn and apply knowledge with physical or virtual robots will be really important. It’s 5 years now since the IBM Watson system beat the TV game show Jeopardy, now doctors are training Watson in how to recognise and diagnose illnesses.

3. Data Security; the weak spot in all systems that need customer data is that the customers become too scared to share their information – scared of data leaks and hacker attacks. The Ashley Madison attack in 2015 was an example of how hackers can even threaten the existence of a company, just by stealing data.

Big Data, and data analysis in general, will certainly be more important in 2016 because it is now affecting so many companies, but this final point is important. As customers share more data there is the danger of more leaks and more attacks. The only thing that will prevent the benefits of enhanced data analysis becoming a reality is if people become wary of sharing information.

Big Data Is Now A Corporate Asset

IBA Group
Mark Hillary

Big Data is growing up – finally. That’s the conclusion of new research published recently by the Economist Intelligence Unit (EIU). The research details how corporate attitudes to data have changed in the past four years – with many organisations now seeing data itself as a corporate asset.

Instead of constantly seeking more data, companies are asking the right questions. They are seeking the right data that can help decision support, rather than measuring and capturing everything regardless of use.

This strategic alignment with a more intelligent approach to data often comes with the elevation of a data manager to the executive board. Either the role sits with the CIO/CTO or a new Chief Data Officer role is created to ensure that there is always a view on data value at the top table.

What is particularly interesting for managers who are asked to invest in Big Data projects is that there is a link between a well-defined data policy and financial success. Not only does a well-defined data policy correlate with business success, but also the effectiveness of being able to resolve real business problems through more effective data use.

Commenting on the EIU research in Forbes magazine, Bernard Marr, author of the book “Big Data”, said:

“As technology continues to improve, the ‘bigness’ of big data will become less and less of a factor. Companies are becoming more comfortable with the idea that they will need to scale up to allow the value of data initiatives to reach all sectors of the business, and so they are becoming more comfortable with approximation, agility and experimentation.”

I agree with Marr. We can see from this EIU research that more companies are exploring how to use Big Data, but importantly more are finding a genuine business reason or use. As more companies find these reasons to get more engaged the use of Big Data will explode in size – all over the world.

IDC: Big Data Spending To Soar Over Next 5 Years

IBA Group
Mark Hillary

Concerns have been mounting in the Internet of Things (IoT) recently. Equipment manufacturers have been tussling over standards prompting some to believe that a ‘Betamax’ situation may be created where some devices cannot connect to the IoT grid.

If such a situation occurs it could seriously impact the adoption of Big Data projects. Big Data does not depend on the IoT – there are many other types of large database – but the constant flow of IoT data means that most IoT projects will also require a Big Data element.

However there is some good news from the analyst community. New data from IDC suggests that the growth rate for spending on Big Data between 2014 and 2019 will be just under $50bn – that’s compounded growth of 23.1% each year.

The real elephant in the room for the Big Data market is the security of collected data. There have been several damaging data leaks by major organisation in recent months. The danger for companies that are collecting large amounts of data is that leaks of private data will cause brand damage so serious that companies could even face an existential threat.

IDC believe that large companies are aware of this danger and are planning their Big Data infrastructure with security in mind.

“The ability to leverage big data and analytics to develop an integrated view of customer activities and business operations will provide competitive differentiation to companies across industries,” said IDC programme director Jessica Goepfert.

“However, in addition to the huge opportunities, big data presents some significant risks and liabilities to organisations. Line of business and IT executives will need to approach these ongoing challenges with awareness, flexibility, adaptability, and responsibility.”

This is an area of the technology business that is growing by around one quarter every year right now. There will need to be some big mistakes to derail this market, but it is possible. The constant stream of security stories in the media shows that the public are more aware than ever of the dangers ahead. Companies adopting Big Data need to ensure they are always one step ahead of the data thieves.

European Financial Regulators Investigating Big Data

IBA Group
Mark Hillary

One of the key advantages for brands mining Big Data is the information it can reveal about their customers. Trends can be spotted and in many cases actions by customers can be predicted before they take place.

This is particularly applicable to financial services because records of financial transactions are thorough. Financial service companies can use customer behaviour to predict the best time to offer a new product – such as a loan – or even when a customer might be struggling and about to default on financial commitments.

But European regulators are pushing back, concerned that if companies can analyse data and create predictions that can be used to sell additional products then it may be seen as an invasion of privacy by some customers.

The three EU financial regulators – the European Banking Authority, European Securities and Markets Authority, and European Insurance and Occupational Pensions Authority – have joined together to study the effect of Big Data on customers in Europe. There is no formal data announced for their report, but they have indicated that they will be studying Big Data closely for about the next year.

Banks and insurance companies have many legitimate uses for Big Data that go beyond just marketing alone, fraud prevention for example, so it will be important for companies using Big Data to explain the benefits to the regulators over this coming year.

If the regulators conclude that analysing data in this way is invasive, it could create a problem for many banks that are now investing heavily in this technology. It’s up to the industry to demonstrate their need.

Could Big Data Help Improve Your Journey To Work?

IBA Group
Mark Hillary

In November 2014 I was lucky enough to be invited to Minsk to visit the IBA development centre. I visited with the Ovum analyst Peter Ryan, who was over from Canada and possibly not feeling quite as cold as I was, after arriving from the Brazilian summer.

One of the projects I remember most from that visit was the ticketing system for the Minsk public transport system. IBA designed a complete solution for the bus and metro network that would comprise the cards, the card readers, the recharging systems, and all the software needed to make the system function. It was far more than just a software project and really showed how companies need to approach business solutions rather than technical challenges.

But the most interesting thing about the public transport system was not how it was delivered; rather it was what could be learned after implementation. Suddenly Minsk City Authorities had access to information on every bus of metro ride taking place across the entire city. When, where, and how journeys were being made was suddenly all being recorded and could be analysed.

The reality was that the data created by the software and hardware system was probably worth more than the system itself.

I was reminded of this when I saw in Forbes that commuters in Stockholm, Sweden, will soon be able to access similar data on the travel patterns in their own city. With the data on Stockholm travel passing through a Big Data analysis engine, it should be possible for commuters to see what will be happening on the public transport system two hours in the future.

This ability to predict the future will allow customers to change behaviour and avoid hot spots. Naturally this will change the predictions, but the system will be able to revise predictions in real-time.

Some commuters have complained about the move away from paper tickets and cash payments, but when anonymised commuter data can be collected and analysed in this way, new benefits become clear. I know that I would love to be able to see how the transport system will look where I live, even just one hour in the future.

Companies with Big Data expertise and city governments have the power to make the life of commuters so much easier – let’s hope more cities copy the example of Stockholm and Minsk.

Healthcare Is the Big Data Growth Engine

IBA Group
Mark Hillary

In July this year, I ran 153km. My doctor would probably be pleased to see this, as it’s quite a good average of about one marathon every week. I was hoping to do even better in August, but I’ve not been very well so my figures are lower.

I know the distance covered because my iPhone has the Nike+ app. Not only is it recording the distance each time I run, but I can see where I went, the hills covered, the split times, average pace, the weather, and the type of terrain covered. Add an extra accessory, like the Apple Watch, and I could be tracking and recording my heart rate too.

Tools like this are the reality of concepts that we all see in technology journals – Big Data and the Internet of Things are two concepts that we read about all the time and yet they are often undefined or unclear.

Take another example related to health. The games company Nintendo is in the process of launching an entire suite of products related to “Quality of Life”. The first one is a box you can place by your bed as you sleep. It does not need to touch you, it just needs to be close, maybe by your bedside light and book.

The device monitors you as you sleep. It gathers data over time and compares it to other people and can recommend how you can improve your health. The device can give concrete advice (usually related to exercise or food) based on knowledge of the way people sleep and it does not even need to be worn.

All these devices are capturing enormous amounts of data that we never used to capture. In theory, open sharing of health-related data with health professionals should make their life easier and improve diagnosis for patients.

But it’s not always as easy as the technology suggests. A new paper in the IEEE Journal of Biomedical and Health Informatics explores Big Data use in healthcare and why it is taking longer than expected to achieve the promised benefits.

The real challenges are:

1. There is just so much data that is being stored. Most individual healthcare providers don’t know what to do with all the data they have – at that is just at individual company levels.
2. Finding a way to use the data is difficult. Most healthcare managers are not experts in the concepts of IoT being used to create data and Big Data expertise allowing the study of enormous databases.

The “Holy Grail” for healthcare providers is to be able to create an “Electronic Health Record”… a single key that then allows every possible piece of information on a single patient to be indexed. This would include traditional patient notes, but also any X-rays, MRI scans, performed over a lifetime. It would also include extra information, such as sleep patterns from a Nintendo device, exercise records from a Nike device, and a record of your pulse from the moment you are born to when you die.

Technologically we are there already. Mainstream equipment such as smart phones and smart watches are already making the data collection possible, but can the healthcare companies actually make sense of all the information they can access?

At present no, but it goes to show that healthcare is about to be one of the growth industries of the century. Populations are getting older and information technology is blending with normal life in a way that nobody could have imagined a decade ago.

Big Data and the IoT have a real and definable purpose in healthcare. Where do you think the next big healthcare innovation will take place?

Big Data Market Set to Grow 600% by 2019

IBA Group
Mark Hillary

I have talked a lot about Big Data on this blog. It is a technology that is now becoming normal and accepted in the enterprise, largely because of two factors:

1. The Internet of Things (IoT) means that every electronic device is becoming connected. Even light bulbs can now be assigned an IP address so you can connect them to a home control system. All these connected items generate vast amounts of data…

2. Consumer behaviour and their relationship to brands has been entirely reversed in the past five years, from brands offering a way to get in touch to consumers defining exactly how they want to review or criticise products. Now brands need to seek out comment and to engage wherever the customers are located.

There are many more factors, but I believe that these two broad changes are responsible for creating enormous amounts of data – amounts that seemed unfeasible a decade ago.

The industry analysts support this view. Ovum recently announced their own research, which indicates that from now until 2019 they predict that the Big Data market will grow 50% each year. Compounded annually this means that by 2019, the market for Big Data software and expertise will be six times bigger than it is now.

Six times. That’s a lot of market growth. The Ovum Big Data Practice Leader, and co-author of the report, Tom Pringle, said: “The experimental era of big data is coming to an end, organizations are formalizing their use of big data technology to realize the business value they expect to find.”

The important factor to note here is that Ovum is suggesting that the time for experimenting with Big Data is over. Many companies have tried it, toyed with open source software and systems, and experimented with the insights they can gain from Big Data analysis, but it is now proven that many companies need these insights.

The time has come to call in the experts.

Making Sense of All That Data

IBA Group
Mark Hillary

In my last blog I mentioned that Big Data has progressed far beyond just being a business buzzword. There are entire industries being shaken to their core because a leading player finds a way to analyse their customers better than their rivals. Far from being a management trend, this is a strategy that will fundamentally change many industries.

But have you ever stopped to appreciate just how much data we are creating today?

Some excellent analysis in Business Insider recently explored this question. The problem is that people and companies are just creating so much data – it is increasing at an exponential rate. At the present rate we are doubling the amount of digital data that exists every two years.

But even though we are creating and storing these enormous amounts of data, only 0.5% of it is being analysed. There is so much data out there that companies, governments, and individuals feel swamped, unable to gain insights from it.

The Business Insider article features a comment that cuts to the heart of the Big Data issue: “You have to start with a question and not with the data,” says Andreas Weigend, former Chief Scientist of Amazon, now director of the Social Data Lab and lecturer at UC Berkeley.
Businesses need to start thinking about the insights they could get from their customers, to ask more ‘what-if’ questions. There are solutions out there in the data, but it is impossible to analyse every byte of data.

A typical analogy for the average person might be the difference between email and Twitter. You check every email, even if it is only long enough to decide that it should be deleted. However, you only check Twitter messages that are arriving as you are looking at the news stream, or you use intelligent filters and analysis to ensure that interesting messages are made visible.

Businesses need to start thinking of their Big Data strategy in the same way. How can insights be drawn out from the data they already have?

Big Data Means Big Business

IBA Group
Mark Hillary

Big Data is still just a buzzword for many people. Magazines and newspapers that do not cater strictly to a business audience continually need to explain what they mean when talking about the subject and the strong association with technology means that even some business leaders are still unaware of the true benefits.

But as with all technology projects and ideas, if they can be associated with actions that can improve a business, make it more efficient, deliver services faster, or create new products before competitors, then the leaders can see the advantage.

Forbes magazine recently documents a few examples that demonstrate some of the advantages. Carnival Cruises needs to plan the best way to serve passengers in much the same way as an airline does. However a cruise is a much longer journey than a flight and across all their ships and passengers, Carnival has 80 million cruise days per year. If they could just earn $1 per day extra from each passenger then that’s an immediate $80m boost to revenue.

That’s an example of how to analyse customer behaviour so products and services can be targeted more effectively. Retailers still do this with loyalty cards, although the idea of a loyalty card has been falling from fashion in recent years – customers are tired of giving away their personal data in return for very small benefits.

But data can also help to save money and improve service too. The Australian telco Telstra uses Big Data analysis on their entire network with predictive analysis so potential faults on lines, and in specific areas, can be identified before they happen. Outage time is reduced, engineers can be moved into position faster, and not only does the company save on maintenance, but the customer is happier too.

Every big business uses data today. Every business has the opportunity to analyse this data in a more effective way. There is always information available if you know how to dig deep into the data you have.

Business Intelligence is Being Led by Data Intelligence

IBA Group
Mark Hillary

The analyst firm Gartner recently published some fascinating data trends in Forbes magazine. They summarised how important Big Data is becoming for business intelligence in three clear trends:

1. By 2020, information will be used to reinvent, digitalize or eliminate 80% of business processes and products from a decade earlier.

2. By 2017, more than 30% of enterprise access to broadly based big data will be via intermediary data broker services, serving context to business decisions.

3. By 2017, more than 20% of customer-facing analytic deployments will provide product tracking information leveraging the IoT.

These trends are exciting because what they point to is how communication is changing between individuals and how this is now affecting the way that companies do business.

Mobile, social, cloud, and shared information are all forces that have really only grown in importance over the past 5-6 years. Many company leaders have not realised how all these factors will change the way that companies do business and how decisions from new products to choosing a partner company will all be data-led.

The Gartner predictions are point at corporate behaviours just 18 months in the future. Have you explored how your own organisation is using data today and if not then can you be sure that your competitors will not be making better business decisions a year from now?

Will Social Networking Transform Customer Loyalty?

IBA Group
Mark Hillary

In my last blog, I mentioned that social networking technologies are changing how many companies use CRM. Opportunities are created to have a much deeper relationship with customers than was ever possible before and this goes far beyond just CRM alone.

But what is it that any company really wants? Why do they invest in all these technologies in the first place? There are many reasons, such as improving the customer experience, but possibly the most important is to generate customer loyalty. It costs far more to attract new customers to your business than to just keep the existing ones happy, so managing loyalty is important.

And as customers we all know about loyalty schemes. You probably have loyalty cards for your favourite hotel chain, airline, coffee store, bookstore, and supermarket. Every type of business tries giving away points and prizes to encourage loyalty.

The problem is that academics now believe that our present focus on loyalty through loyalty programmes doesn’t work very well. Take airlines for example. There are really only three major airline alliances, Star Alliance, One World, and SkyTeam. Serious business travellers just take a membership with all of them so they always collect points regardless of the airline used.

Most people use the supermarket that is closest to their home rather than travelling much further because they have a loyalty card from another store. Most of the time these loyalty cards don’t really create very much brand loyalty.

Smart companies today are looking at their CRM data and using a ‘buzz monitoring’ platform to analyse the social networks and then interacting with customers based on the information they can glean from the customer behaviour data. In effect, what is happening is that companies who know their customers well are able to use the data to create customer loyalty gifts and rewards that are targeted at the individual customer – not just points that every customer earns.

This is a big change in behaviour for many companies and it will be the back office technology that drives the information for this to work, but it is a natural shift. Customers have greater expectations on brands today and the first time a brand responds and rewards you in a unique and individual way will create a ‘wow’ moment for many customers.

It is these interactions based on data that will drive customer loyalty in future, not loyalty cards. Has any major brand ever rewarded you based on their knowledge of behaviour and how did that make you feel?

Mixing Social Networking with CRM

IBA Group
Mark Hillary

Social media is maturing and becoming an important part of the supply chain for many businesses. In areas like the media it is clearly a strong communication channel between content creators and their customers, but in other industries there has been an even deeper use of the technologies.

Take retail as a good example. For decades retailers have combined loyalty cards with CRM technologies to try predicting customer behaviour and to drive loyalty to certain products. There are many examples of retailers knowing individual customers better than their own family because of the data collected during their shopping trips.

A famous example is the US retailer Target sending discount coupons for products a new mother might want to a teenage girl. Her father was outraged, but he apologised to the retailer when his daughter confessed that she was in fact pregnant. The CRM system knew it before the father.

But traditional CRM has always relied on actual purchases and visits to the store. There had to be an actual interaction with a retailer to generate data that could then be analysed. With social networks and social media uploads customers provide information on their likes, desires, and preferences without even visiting the store.

This is a fantastic opportunity for retailers who can integrate social channels into their existing CRM. In addition to actual purchases, discounts and offers can be tailored to include preferences and the general sentiment of an entire group of customers.

It does require a different approach. Some kind of community management is usually needed for the retailer areas – such as the corporate Facebook page – and new software capable of ‘buzz monitoring’ other areas of the Internet has to be applied. But the opportunity for retailers of knowing their customers even better through the use of better technology systems is clear.

The same opportunity exists across all sectors – try searching for online discussions about your company name or products today. I’m sure you will find people talking about them. Now the question is, are they saying good things and if not, what do you do next to engage those customers?

Are you engaging with customers using social networking and how different is this data-driven approach to the old idea of a customer service team?

When Will CRM Finally Work Properly?

IBA Group
Mark Hillary

Companies such as banks have complained for years that their Customer Relationship Management (CRM) system doesn’t really work. The systems are expensive and yet they rarely return what was promised when the sales team demonstrated what could be achieved.

But I think that often, the real point of CRM has been lost somewhere between the software company sales pitch, the implementation, and the end user trying to make sense of how the system operates. A recent article in The Financial Brand magazine lists 6 important reasons why you should be reconsidering CRM. The first reason asks these questions:

“How will the data in the CRM benefit my customer?”
“How can I use this to speed up our process, to benefit my customer?”
“What events could be triggered using this data to help my customer?”
“Is there info that can be gained from the data that would help me do what is best for my customer.”
“How can my sales team best use the data to identify opportunities to help my customer?”

I entirely support this view. If the CRM system is not entirely focused on planning how processes and data can benefit the customer then there is no value in the system.

I would go further and argue that with the abilities we now have, CRM expectations should be much higher. Think of your mobile phone company as a good example. They probably offer you a monthly tariff on a fixed contract that offers a certain amount of minutes talk-time, texts, and Internet access.

But if you use too much Internet time or talk too much the customer usually gets hit with penalties – or very high per minute costs.

Yet, why would any company want to do this to a customer? You want to help the customer, not hit them with penalties surely? Why not use the data that you have on how this customer behaves – how many minutes they use on average each month, how much Internet data they use – and offer a special tariff designed just for that individual customer?
We have the Big Data expertise to do this and the CRM systems, but there has rarely been a connection between the data and how it can truly help the customer. For companies that want to succeed today, this has to change.

Crowdsourcing and Big Data Can Come Together

IBA Group
Mark Hillary

Could Big Data help the buses in New York run on time? That’s what one city politician is hoping for. New York City Council Member Ben Kallos has campaigned for the Metropolitan Transit Authority (MTA) to openly release all their data on bus arrival and departure times.

Kallos is convinced that the buses never run on time. When he has complained in the past to the MTA they have always suggested that he is wrong. He managed to obtain three months worth of bus data and with the help of some data analysts he proved that the buses only ran on time 58% of the time.

The MTA has pleaded that the data is in a difficult format for it to be quickly released to the public so his project has not moved further than this pilot stage, but this demonstrates the power of citizens and politicians understanding how much data is available from public bodies.

London has released live position data for their buses for several years now. Anyone can create a Google map like this, showing the real-time position of all the buses in the city.

Some of these online maps may appear to have no purpose other than to astonish the viewer – look at how much data is available! However, when politicians start using Big Data projects to help citizens then the value of Big Data is clearly going mainstream and being understood by the general public.

Did We Forget How to Query Databases?

IBA Group
Mark Hillary

Author of The Analytics Revolution, Bill Franks, recently wrote a fascinating exploration of database structure in Forbes magazine. This might sound like an oxymoron – database structure and interesting – but bear with me.
When most people think of databases they think of relational data – fields of information. A database captures specific information such as name, address, phone number, all in a certain way so each field of information conforms to certain standards such as type (text or numbers) and length.

If you have never designed a database then think of it like this, you have rows of information that are the records of data – let’s say each one describes a customer. Then you have columns of information, each one is a field of data like a phone number or email address. So each record contains many fields… each “person” has a name, phone number, address… and so on.

For many years now the standard way of querying a relational database like this has been SQL – Structured Query Language. SQL is a series of commands and tools that make it possible to logically extract information from a database, in simple terms if you want to extract all the entries from a list of personal details where the date of birth is before 1980 then it’s a simple query. It’s just like asking a question and the database returns the answer.

But in the world of Big Data most of our assumptions around how a database is formed and how we can query it are different. There may be no fixed structure in a universe of data that is constantly expanding and changing. This makes the process of querying a Big Data set very different.

Of course this has been well known and many tools already exist that help to support Big Data analysis, but what Franks is arguing is that the skills and tools we need today are what we used to have before SQL became accepted as the standard way to interact with a database. Before we got all organized and relational, people had to query data in a much less structured way.

His book addresses this in more detail, but I find it fascinating that we can sometimes forget what we already knew about accessing data. Perhaps there will be a greater demand for people who can remember how data was queried before SQL became commonly used? It’s an interesting idea and goes to show that, in technology, the new is not always new.

The Big Picture on Customer Service, CRM, and Big Data

IBA Group
Mark Hillary

Last month I was in London, invited to speak at an event hosted by the IBA Group. The theme of the event was the resurgence of CRM and how it is being combined with Big Data and becoming an important part of corporate strategy today – particularly for companies planning how to improve their customer service.

The analyst Peter Ryan from Ovum was up before me. He talked about the strategic use of CRM and how the improved use of information feeds into a customer service strategy. Ovum has predicted that improving the customer experience will be even more important than improving revenues for companies in 2015 therefore this theme is taking on a new significance.

The director of Internet Solutions at IBA, Aliaksei Minkevich, was also speaking. He described some case studies and drove home the real importance of thinking about technology projects and how they can improve the way a business uses data. Aliaksei was particularly focused on describing how a technology solution is no longer as simple as it used to be. Much of the business benefit from processes and systems today comes from the opportunities to use information in a smarter way, rather than just reducing cost or aiming for efficiency.

I started talking about the connection – as I see it – between modern day CRM and Big Data. The way customers interact with companies in all industries has changed in the past decade and this wider social change in how people communicate has to be appreciated by corporate executives.

The two big drivers of this change were the launch of the iPhone in 2007 and the explosion in the use of social networks from 2008 – both very recent dates. Of course it was possible to use the mobile Internet before the iPhone, but Apple made it so much easier and easy access became the expectation from consumers.

And, of course, people were using social networks prior to 2008, but this was when it really went mainstream. Facebook started maturing and Twitter became commonly mentioned in broadcast media, such as radio and TV. 2008 was really the tipping point when social networks became normal for everyone.

These developments have changed the way customers interact with companies. It is now fairly normal for any customer to use at least six different channels when interacting with brands – email, voice, chat, Facebook, Twitter, and review or rating websites like Tripadvisor. There are more and this changes all the time, but this is already a very different environment when compared to those days before social networks and the mobile Internet were common.

So companies should no longer be exploring how to improve customer service as an activity, they need to be working harder at Customer Relationship Management – back to CRM again. This is because the real measure of success with customers in this multichannel environment is the quality of the engagement between the brand and the customer.

Getting this right demands the use of some serious technology. Running a customer service team no longer means just answering the phone, it needs data analysts, knowledge of Big Data, and a CRM system that allows the customer to engage and enjoy interacting with the brand.

Companies that can deliver this kind of technology in a way that improves the experience of your customers are going to lead the way. Tech players will become customer service experts as the use of technology underpins how companies interact with their customers.

Underneath all this remains the fact that how we all communicate has changed. If you want any executive to understand why this is important, then just ask them about the last time they needed to select a politician to vote for, a restaurant to eat in, or a hotel to stay in. If all these decisions are now being shaped by data, then don’t you think that the relationship between your own customers and your company are also about to be shaped the same way?

 

Big Data and CRM

We have it all in this London event featuring international speakers

It’s good to explore the future. At IBA we are always looked ahead to what is coming next, this is one of the reasons why we host this blog. It’s also why we have arranged an exciting event in London titled “The Big Picture on Big Data and Customer Relationships: Case Studies and Thoughts for the Future.

We have three great speakers lined up for the event.

Mark Hillary is an IT director who became a writer. His most recent book explores the subject of CEOs who blog, but he has also written about outsourcing and the globalisation of services. Mark is based in Brazil. Mark will talk about how Big Data and the analysis of customer information is changing the way companies are structured.

Peter Ryan is a principal analyst at Ovum. He is one of the best-known global analysts focused on customer service and experience. Peter is based in Canada. Peter will talk about the way that CRM is changing customer interactions and how companies relate to customers.

Aliaksei Minkevich, the director of our Internet Solutions Division will present some case studies of our own work in this area. Aliaksei is based in Belarus.

All three speakers are travelling to London to share their ideas and we are thrilled to host this event. It will take place on November 27 at the Institute of Directors in London.

Big Data as part of business in 2015

IBA Group
Mark Hillary

Big Data sometimes appears to be a solution that is looking for a problem. It sometimes looks like a technology that has very little use in the real world of business and technologists are rushing around the world looking for examples of how it can be applied.

But I was having a conversation this week with a Big Data expert and I asked a question about customer service in retail – isn’t this one of the areas where Big Data is having the most impact. He agreed that it is one of the most affected industries, but for several reasons.
Everyone knows that customer service in just about every industry has changed. Consumer goods used to feature a telephone number or email address you could use to ask questions or complain. Now customers will use many different channels to comment on a product and many of them have no direct link to the manufacturer.

Customers today are familiar with at least six channels when contacting brands; email, voice, chat, Twitter, Facebook, forums and review websites. These are just the main channels being used now. Many brands are interacting with customers on other social networks, such as Pinterest or Instagram, and other communications tools, such as Whatsapp, are rapidly being adopted.

So customers are using many different ways to communicate. Often there is no formal notification to the brand involved – the brand is just expected to find the question online.

And now consider the retail industry. All these communication changes are taking place, but also the way people want to purchase items. They might buy in-store, online for delivery, online with collection in-store, they might want to return or exchange an item in-store even though it was purchased online.

The communication chain between a brand and the customer is far more complicated than a decade ago, but so is the supply chain. Enter Big Data. These real-life business problems are exactly where Big Data is moving from concept to daily use.

If you want to analyse a complex supply chain in real-time and explore how your customers prefer to shop, how they behave, where are items missing, then all these questions can only be analysed with an enormous data set that is constantly changing.

Likewise for the communications with customers. If they are communicating anytime from anywhere on any channel then there is an analysis function you need just for monitoring communications, but by employing Big Data techniques you can also predict and focus on the most important channels.

I think that 2015 will be the year when we finally stop talking about Big Data as the exception and start considering it just a part of business as usual – in any industry.

Could Big Data help to prevent the spread of Ebola?

IBA Group
Mark Hillary

I’ve written about Big Data in several blogs here. What it is. How it can be defined. And even how it can be used, but there are two additional factors that really help with any understanding of how Big Data fits into the modern organisation.
How do you make it work – what tools are needed to move from just having a large amount of data available to being able to gain insights from that data?

Do I have the kind of data that I can get insights from? What kind of insights am I expecting from the information that I have?
I have added two links to recent news stories that can elaborate further on these questions.

It is no use to anyone if you just have an enormous amount of data, but no tools to analyse it with. You can’t engage with Big Data using an Excel sheet. The volumes involved are often enormous and far more than what you could load into a computer to be studied as a single block of information.

So this is one of the first issues to address, and it may be where an expert partner can help the most. Is your data available? What tools can you use to collect together all that structured and unstructured data, and how can you even start to analyse it?
Now, what are the kinds of insights you can find? It depends on your business and the type of data available, but with Big Data you can uncover all kinds of relationships between variables that were not visible without the analysis.

This example of how Big Data is helping to predict where Ebola will strike next is a great example. It is just taking information we already have such as infections, locations of hospitals, number of doctors and so on, but using past knowledge and these factors to make predictions. Now imagine if you could start applying these insights in your business?

Making Big Data work with the right tools and determining the type of insight you need are two important factors in planning how you can make it work for you.

Will a Skills Shortage Threaten the Future of Big Data?

IBA Group
Mark Hillary

As the economy develops, old jobs vanish and new ones are created. This process has always taken place as technology creates new needs and old skills are replaced. Just consider how important the blacksmith used to be before cars were commonly used and if someone described themselves as a blogger or flash developer in 1985 it would have made no sense – times change.

Big Data is another of these major changes. Not just in the sense that we are becoming able to analyse larger sets of data thanks to the technology becoming faster and more powerful – especially with more memory being available, but because the ability to do this work is now a skill itself. Understanding Big Data and being able to manipulate and analyse large sets of data is a popular skill to be exploring now as every analyst predicts that Big Data use is set to explode in the coming years.

The analyst firm IDC wrote a study in 2012 that predicted the amount of data available to analyse would increase 50 times by 2020. This prediction remains true – if anything it may be even more by 2020 as new applications that create data are launched all the time – from smart watches to other wearable technologies.

All this has led to a fear that there will not be enough people available to work on Big Data projects. McKinsey believes that the US will need almost 200,000 new data scientists by 2018 and the British Royal Academy of Engineering has predicted a need for 1.25 million graduates in science and technology subjects by 2020.

A recent column in the British ‘Daily Telegraph’ claimed that this shortfall in data scientists might even be a threat to the future of business. But what all these concerns in the UK and US often fail to acknowledge is that there are many other countries with an abundance of data scientists.
Offshore outsourcing has been long proven as a strategy for software development and other IT requirements. It will be exactly the same once data science becomes a mainstream part of every business. And companies like IBA Group are already doing it today.

Defining Big Data

IBA Group
Mark Hillary

We have talked about Big Data on this blog before and tried to define it in a way that doesn’t require complex terms, but it is not easy. Many people have very conflicting views on what Big Data is and how their company uses – or will use – it.

A fascinating feature article in the business journal Forbes explores 12 different definitions of Big Data, starting right from when the term was initially used in the 1990s. That’s right, we were all talking about Big Data back in the 90s – it’s not a recent term. The first known recorded use of the term was in a paper published by NASA in 1997 describing their problems of trying to work with enormous data sets that could not be loaded into a computer at once.

The Oxford English Dictionary is possibly the best place to turn for a simple non-technical definition: “data of a very large size, typically to the extent that its manipulation and management present significant logistical challenges.” That’s clear and focused, but also doesn’t really give away any clues about the scale of the challenge faced when manipulating many Big Data sets.

Wikipedia uses a very similar definition to the OED, but the advantage of Wikipedia is that the crowd updates it regularly. As attitudes to Big Data change in the IT marketplace, the online definition can change. The latest Wikipedia definition (last updated on Sep 1) says: “Big data is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process using on-hand data management tools or traditional data processing applications.”

Is it possible to define big data inside 140 characters? If you can, then why not tweet your answer to @ibagroup?

Is Jargon Preventing an Acceptance of Big Data?

IBA Group
Mark Hillary

The Smart Data Collective blog recently published a view that there is too much jargon circulating in the industry related to Big Data. In fact, as I mentioned in my last blog, Big Data is itself a term that is often misunderstood and needs more clarity.

The blog is interesting because the author takes a good example of an over-used business term, ‘digital’, and explores what we mean when we read and use this term. Many of the definitions from the dictionary have nothing at all to do with the definition of digital business you might expect – modern, hi-tech, and connected.

In fact, many more terms are taken from the dictionary and bent and shaped into something new by technology companies. Innovate, disrupt, and thought leadership are all terms that mean something different if you are not working for a technology company, but how can we improve the use of Big Data as a term?

The advantage we have is that Big Data is a genuine and meaningful area of data science. It’s not just jargon created for use by MBA students as they discuss their plans for ‘wealth-generation’.

Big Data needs to be understood by the general public and by the company leaders that have never really felt that they had to understand technology before. But almost everyone has now used Facebook, or contacted a customer service centre, so it is becoming easier to connect the theory of how Big Data can be used to the ways in which people see it every day.

Understanding Big Data

IBA Group
Mark Hillary

Big Data is a subject we have explored often on this blog because it’s an area where IBA has extensive experience and knowledge, but it is often difficult to explain. How big does a database need to be before it can be considered ‘Big Data’ and why do we need this separate terminology to refer to manipulating and analysing this data when relational databases have been in use for decades?

One example that goes a long way to answering these questions is the way that customer service is changing – especially for retailers. Products used to have a phone number and email address that customers could use to reach the manufacturer or retailer – usually to complain after a purchase.

Now, customers use online forums, review sites, Twitter, Facebook as well as the more traditional and direct channels such as online chat, emails, or a voice call. Customers are not always directly contacting a brand when they comment on a product, yet they usually expect a response.

Exploring this mass of information is a classic Big Data example. The retailers want to connect together all these communication channels into an ‘omnichannel’, yet this is impossible when they are considered to be regular databases.

If a customer emails a complaint, then tweets about the problem because their email is not answered and then finally calls because neither tweet nor email has been answered then the ideal situation for a retailer is that the agent on the phone knows about the earlier email and tweet.

But to make this work is not easy. The company has no control over Facebook or Twitter – it’s not internal data. And how can comments on a tweet be connected to a customer on the telephone?

All this is feasible, if you have enough information from various sources and you can analyse it quickly enough. Every company that interacts with their customers is now exploring this problem so maybe Big Data is about to hit the headlines again.

Big Data and Cloud in decision-making

IBA Group
Aleš Hojka, CEO of IBA CZ
Vitězslav Košina, Business Consultant at IBA CZ

It is a reality today that organizations have to deal with a multitude of unstructured documents and other data. These data have true value, if they are properly and timely processed and extracted, and also are supplied with really useful links.

Almost any business has in some way implemented a data management system (DMS), a content management system (CMS) or a business intelligence (BI) solution. Unfortunately, a new system often provides a very low added value, especially when a large amount of data is involved. Getting reasonable output from unstructured data is problematic. Why is it so?

DMS, CMS, and BI systems can be really effective, if they meet two essential requirements. The first is a sufficiently flexible environment and quick access to information complemented by strong information security. A really flexible environment shoul be able to respond to resource and computing requests in a very short, practically in real time. This can be easily achieved by using a cloud-based solution. As these requests are dynamic and cannot be easily predicted at the time when the system is designed, cloud can be very instrumental. In addition, keeping resources for a «rainy day» is not an effective allocation of resources.

Therefore, cloud is a prerequisite for dealing with big data, but it is not the only one. In some cases, data and documents are not available anytime and anywhere without limitations, though we have an environment designed for large amounts of data. This is true.

It should be noted that effective decision-making involves an increasingly growing amount of information. As the information should be available on mobile phones and tablets, an information management system cannot transfer huge amounts of data and should have short response time. If we meet these two basic requirements, then we are poised for truly efficient extraction and processing of large amounts of data, which can be further aggregated and analyzed to make a grounded decision, deal, and etc.

For many companies, using Software as a Service (SaaS0 is a problem, because they have to do with sensitive commercial information or client data. From the perspective of a cloud-based solution, a dedicated cloud is needed as apposed to shared capacities.

Many organizations outsource only the infrastructure, while we recommend to outsource the entire solution. With a cloud solution, the issue of security is solved to the extent that is normal for corporate clients. In this case, only the needed capacity is commissioned and there is no need to reserve resources for the team that takes care of the infrastructure and applications. The organization can thus focus on business and management objectives, as well as provide added value to the clients.

With mobile devices, security is a very thorny issue because attacks on their security are more likely than on the computers that are located in the company’s premises, where they are protected physically. The good news is that these devices are so powerful that allow for implementing the strongest encryption and other elements of modern security.

Taking into account the links between documents and their associated metadata, as well as other data sources, cloud computing is the best solution one can choose. It is however possible, if needed, to move from SaaS to the model, in which the solution is managed by the customer and yet not loses the flexibility that cloud offers us in terms of resources. Using cloud is much cheaper than building one‘s own infrastructure. Moreover, it enables organizations to concentrate on their requirements and business needs instead of specific software or infrastructure.

Internet of Things

IBA Group
Mark Hillary

I have written recently about Business Analytics (BA). What is BA? How does it affect your IT strategy and your business in general? I have also observed that there is a relationship between BA and Big Data (BD) – they are related concepts.

To clear up any confusion, I would say that BA is related to taking a set of data, performing a modelling operation, and using the model to predict some kind of future state – what-if calculations. BD is more of a continuous analysis of very large-scale business information.

But the business concept that is driving forward the importance of both Business Analytics and Big Data is really The Internet of Things (IoT).

Even for a fairly short blog post, this is already starting to fill up with three-letter-acronyms so let’s define what the IoT really is. More and more devices are capable of communication using the existing Internet infrastructure. It used to be computers that we would connect to the Internet, then laptops, then smart phones. Now it is tablets, ebooks, televisions, and every corporate electronic system you can think of – from security systems to electricity meters to photocopiers.

This revolution in making almost every device connect to the Internet is the starting point for the IoT. The classic consumer example is usually the connected fridge that can recommend a dinner based on what is inside, though a more useful example might be your car diagnosing a problem and communicating with the service centre without your own interaction.

In 1999, about 250mb of data per person was created each year. By 2012 ten times this amount of data per person was being generated. Data creation is increasing and the speed of increase is accelerating. Every day people are generating data with their smart phones without doing anything – just by switching it on, connecting to the Internet and allowing applications to work in the background.

This change in both the consumer and corporate environment is driving both the need for continuous Big Data analysis and also the ability to predict what may happen next based on Business Analytic tools.

Business Analytics and Big Data

IBA Group
Mark Hillary

Business Analytics is a topic that is often confused with Big Data. While the analysis of Big Data is related to the continuous analysis of business information through an analytical process, they are related concepts rather than exactly the same thing.

There are various kinds of analytics to start with:

Descriptive Analytics: how to gain insight from historical data, creating reports and scorecards that give a better vision of some existing data.

Predictive analytics: modeling through the use of predictive models and machine learning – allowing the system to learn what might happen next based on the data that is being studied usually in real-time.

Prescriptive analytics: taking a large data-set and attempting to create decisions, choosing possible paths, simulating what might happen if certain decisions are taken.

Decisive analytics: this supports human decision-making with very visual analytic information that helps the user.

So the field of Business Analytics is more related to the process of taking data and either modeling outcomes or predicting what may happen next, rather than just attempting to spot trends in a large data set.

Business Analytics is really a tool that can support executives to make better decisions by supporting their decisions with data, rather than just estimates or guesses. By using actual data from the business and modeling potential outcomes based on decisions that could be taken, the data can help to support the direction a business leader should take.

This type of process has existed for a long time, but it has been the creation of vast pools of business data – the move towards a Big Data environment – that has really stimulated the need for improved Business Analytics. The increased amount of data has provided more information that can be analysed and yet has also made it more difficult to reach a conclusion on the right decisions – without better analysis.

Big Data: buzzword or technology trend?

IBA Group
Mark Hillary

Big Data is often viewed as a big buzzword, but it’s a technology trend that is affecting everyone in their daily life – as well as changing the way enterprises need to organise their systems.

Ninety percent of all the data that exists in the world today was created in the past two years, according to analyst firm IDC. The average American office worker generates 5,000mb of data every day just by working on documents, sending emails, or downloading videos. By 2015 the amount of data we are creating now will have doubled – we are exponentially creating more and more data faster and faster.
You might think that these figures sound exaggerated. How could I have created thousands of megabytes of new data just by going into the office today? It’s easy with emails being copied and shared and presentations today requiring more images and more video – the enterprise has moved on from an era where text alone was enough.

The figures from IDC suggest that data creation will have grown by 2000% between now and 2020. And regular consumers create 75% of all this new data. This is because 87% of American adults constantly publish their location – often unknowingly – via their mobile phone and 65 billion location tagged payments are made in the US annually.

As more consumers carry more devices with the ability to measure and record more information, often automatically uploaded to the Internet, there is a sea of data being created and it affects every possible business and industry in every location.

Organisations in many industries are now facing pressure to explore Big Data, to find how they can get value from mining the information they have on clients and transactions, but it needs tools and expertise to get right.

This is one kind of enterprise project where it is almost certainly better to outsource the work to an expert than to try performing in house. You can buy some tools and make an attempt at examining the data you have, but if you don’t know how to configure those tools or where to start looking then your Big Data project might just turn out to be a big mistake.

Visual reporting

IBA Group
Kirill Degtiarenko

We live in the era of Big Data. These days everyone is overwhelmed with information. There’s no time to read and analyze the data that come to us from different sources. This is where data visualization can help.

According to Visual Teaching Alliance, “it is hard to argue with the observation that the generation of students now moving into and through our educational system is by far the most visually stimulated generation… In fact, research shows that 65% of our students are visual learners.”

They say a picture is worth a thousand words and we see how images today seize the online content. People and companies document their lives with photos. The web is turning into a visual landscape.

Data visualization is already mainstream. As a result of visual presentation, complicated and potentially dull information becomes easily understandable and comprehensible.

The BI market is also shifting, from tables and spreadsheets to diagrams and infographics. It is inherent to a human being to perceive visual images quicker than plain text or numbers. We “read” graphical information several times quicker than data in a spreadsheet. The user can see the key data at a glance and therefore make efficient analysis and a grounded decision.

Clarity and ease of grasp make a report efficient. Based on visualized data, it is possible to make a timely and grounded management decision. High quality visualization enables managers to achieve good business results.

A report title should be also catching and reflect the essence of the report in a clear and concise form. Diagrams serve as a good tool for data visualization. Color serves to highlight certain details and make selected data easy to remember.

The following is an example of how a complicated spreadsheet turns into a visual report.

Spreadsheet Visual report1 Visual report 2