"Business Intelligence 2.0" is the term now being used to describe the rapidly growing business intelligence industry which was reported, at Gartner’s Business Intelligence Summit in London earlier this year, to be ‘stepping up’ and becoming a stand-alone corporate function, like Human Resources or Marketing.
Underpinning this development is the fact that customers and shareholders have ever-rising expectations for immediate access to up-to-date information relevant to their requirements. With the need for companies to increase their profits through shorter sales cycles – reducing inventory costs and increasing customer satisfaction – and the need to stay competitive, organisations are now demanding real-time data from their systems as a standard, not simply as a value-add luxury. In fact, whether private or public sector, the need to have continuous access to systems which provide up-to-the minute information in order to drive mission-critical decisions has become a key business driver across most vertical industry sectors.
But how is this possible when the Holy Grail of business intelligence - “a single version of the truth” - is so difficult to achieve?
In reality, businesses have data warehouses that store several different versions of the truth. While all of them are accurate in their own way, each has a different viewpoint depending on which area of the business is leveraging the information. For example, finance may have an accurate picture of where to send customer invoices and overall revenue and cost of sale data, but when it comes to determining the demographics of that customer and propensity to purchase other products and services, that information is likely not readily available in a finance-oriented system. These departmental data warehouses are continually being updated with snapshots of operational data that is in most cases ‘cleansed’ before being loaded into the warehouse This data cleansing process can take from a few hours to several days to complete.
Such high latency can lead to potentially outdated data with limited business value when it comes to critical decision-making. For businesses that rely on low latency data for day-to-day decisions, its availability becomes very important. In cases where BI underpins applications such as fraud detection or cross-selling, high latency is not only inconvenient but can cost an organisation dearly.
Countering that, one of the main pillars of real-time business intelligence is real-time data integration which facilitates the movement of data with sub-second latency across several different systems while still maintaining its data accuracy and integrity.
Take, for example, the situation where data integration is critical to providing optimal customer service and driving new revenue potential. A customer might contact their cable and Internet provider when they’re experiencing spotty service not only for their newly purchased satellite high definition television, but also with their Internet access. When they make this call, they expect the call centre representative to be able to quickly look up their customer details and set up an appointment for the service technician to come out, and they expect this to take no more than a few minutes out of their busy day.
However, if the customer doesn’t get the level and speed of service that they expect from their provider, they may decide to switch to a competitor. But if the call centre representative has the ability to quickly look up their customer profile, address, and at the same time estimate how quickly a technician can be onsite -- all on the same phone call – the customer is likely to be satisfied with the high-quality service while the cable provider can maximise its call centre representatives' and field technicians' time. At the same time, while on that same phone call, the ability for the call centre representative to up-sell that customer regarding a special offer is much easier than trying to reach that particular customer at a later date, especially with their up-to-date history and preferences right in front of them.
However, regardless of the system considerations and BI software capabilities for the data warehouse, organisations still need to populate it with the most relevant, accurate and up to date information in order to support the business’ needs. After all, once you take away the hardware and the software, what differentiates a company's approach to integration is how it takes advantage of that data, how it processes and leverages it across the enterprise, and how the company’s end user experiences that. Creating real-time access to real-time information isn't only a benefit for both IT and the business, but it's absolutely necessary to compete -- and win -- in today's fast-paced business environment.
