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 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.
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?
As I have mentioned in the last couple of blogs Business Analytics (BA) is about using data and models to make better decisions. This can help governments to improve policymaking and companies to develop better strategies. The aim is to use information to improve the day-to-day performance of the organisation.
But what are the real business decisions being taken with BA tools and how does the data analysis process improve the decisions?
– In the airline business, employees and aircraft need to be in the right place at the right time to maximise efficiency. This is a complex planning procedure when things are going right, but when a flight is delayed or a key staff member is ill or a plane requires unscheduled maintenance then the knock-on effect can be huge. Analyzing the possible options is a great example of how BA can influence real decisions.
– Hotels want guests in their rooms as often as possible. Empty rooms in a hotel mean lost profit and a hotel that quickly sells out a particular night may have been able to charge more for the rooms on that evening. Analyzing past customer behaviour, the competition, and other influencing factors such as big sport or music events in the neighbourhood is another classic example of how data can feed into a specific business decision – how much to charge for a room.
– Banks and finance companies need to make quick decisions about whether to lend money to a particular customer based on limited information – such as the salary. However there are many other factors that could determine whether the individual is good for the loan or not and these can all be quickly factored together to provide a decision.
– Supermarkets always seem to have full shelves these days. Can you remember Saturday afternoons where many big supermarkets would run out of important products? With the entire history of each product and how it sells in each store it is now far easier for supermarket managers to ensure they are ordering the correct stock levels.
These are just four entirely different industries, but in each one it is clear that Business Analytic tools are changing how managers make decisions in those companies.
Better decision-making leads to increased efficiency, a better use of existing resources, and the opportunity to perform better – to earn more by delivering a better service. For this reason, managers in all industries should be thinking about what Business Analytics can do for them.
IDC is one of the leading global industry analysts, so it’s always interesting to see their own guidance on choosing a supplier. Their recent report ‘IDC MarketScape Excerpt: Worldwide Business Analytics Consulting and Systems Integration Services 2014 Vendor Assessment’ focused exclusively on the questions you need to ask when searching for a Business Analytics partner.
1. Pay attention to domain knowledge. Over the years, some service providers have built deep industry expertise across certain business needs.
2. Create a culture of analytics. It is not enough for you to have access to the right data, you need to create the processes that can make use of this data across your entire organization.
3. Don’t neglect the basics. Companies often find they have data issues once the migration has commenced, which will then delay the entire migration project. Stop and avoid all these roadblocks by taking the data cleansing stage seriously so the migration can run smoothly.
4. Align the strength of your supplier with project success. If you find a good match then ensure that your partner gets stronger as the project succeeds.
Of course, point 5 from IDC was to utilize their own research when selecting a supplier. Most of these points are what any manager with a good experience of outsourcing would be planning anyway, but it cannot be stressed enough that good planning for the migration and creating a culture of data analytics are essential for success.
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.
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.