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In a world where customer-centricity is considered vital to continued business success, effectively utilising the vast quantities of information available to an organisation and truly understanding this data is critical to making the right, customer-focused decisions and staying ahead of the competition.
One of the best solutions to this growing problem is to adopt a Business Intelligence (BI) strategy. Nonetheless, many businesses have been slow to focus on BI, something that can be attributed to a lack of knowledge around what is involved, where to start, and of course how long it will take to see any real benefits.
However, BI needs to be an integral part of the enterprise. Especially when one considers that the overriding goal of a BI initiative should be to convert business information into insights and strategic decisions.
In a digitally transforming world, it is not enough to merely have the information available. The insight-to-decision process also has to be swift, meaning a move away from the traditional BI approach, which isolates analytics within a specialised reporting team, hindering the ability to make critical decisions at the speed of business.
On the other hand, the ability to make real-time business decisions will enable the company to kick-start sales, improve the performance of its marketing function, and – crucially – help the enterprise to understand how its customers are interacting with it and how best to reach them.
Remember too that Customer Experience (CX) has become the new marketing battlefront, with CX considered the key way to differentiate one’s business in a digitising world. BI can help improve your understanding of the customer, which will in turn improve overall customer satisfaction and retention.
It can also drive significant productivity and efficiency gains, as it helps to release bottlenecks, refine existing processes, automate routine tasks and bring new levels of organisation and prioritisation to employees’ work. The culmination of achieving all of the above should be a massive improvement in the organisation’s return-on-investment (ROI) across the company.
With the rising complexity of the BI environment, the identification of trends and market developments is a key factor in effective decision-making. It is increasingly important to use the latest technologies and approaches in order to cope with digitisation and market competition.
The first of these trends is the fact that accelerated cloud data migration fuels BI adoption. Increasingly companies are seeing the benefits of moving their data to the cloud, particularly in terms of the added flexibility and scalability at a lower total cost of ownership.
The cloud makes it easier for companies to capture and integrate different types of data, and the greater the streams of information available, the more a BI solution has to work with. Recognising both the value of the data and the ease with which it can all be accessed via the cloud has led to an increasing number of businesses adopting BI.
A second important trend is that of data management converging with modern BI platforms. As more of the workforce uses data to drive decisions, enterprises must ensure accuracy within their data and its use in analysis. Organisations have turned to data curation to address the data management and governance challenges that come with this broader data access.
Data curation is the process of identifying which data sources are needed, putting these in the context of the business and enabling users to interact with it, understand it, and use it to create their analysis. It encompasses the way data is captured, cleaned, defined and aligned, thus creating a bridge between the data and its real-world applications.
A third trend is that enterprises are beginning to understand that true value isn’t measured by the solution deployed, but by how employees use the solution to impact the business. The assumption that everyone is getting value out of a BI platform just because they have access to it can actually be an inhibitor to real progress with analytics.
Finally, there is the understanding that actionable analytics put data into context, and business intelligence platforms are meeting this need by merging with core business operations, workflows and processes through capabilities like mobile analytics, embedded analytics and dashboard extensions. As a result, data workers are able to analyse data and take an action after finding an insight – all in the same place.
In the Gartner Magic Quadrant for Analytics and Business Intelligence Platforms, there are four solutions ranked in the ‘Leaders’ quadrant – let’s have a quick look at each of these:
Microsoft is viewed as a low-priced incumbent with positive sales experience. Its Power BI offers ease of use for complex types of analysis, thanks to integrated, advanced analytics. Furthermore, it is seen as a vendor with a particularly comprehensive product vision.
The second solution in this quadrant is provided by Tableau, and is recognised for its easy visual exploration and data manipulation, as it enables users to rapidly ingest data from a broad range of data sources, blend these and visualise the results.
Third is Qlik, which has recently added several augmented features, including improved self-service capabilities and an Insight Advisor. This company is known for its customer experience and the quality of its peer user community, and continues to extend and enhance its platform as the market evolves.
The final player in this Gartner quadrant is ThoughtSpot, whose key strength is said to be the ability to use search and natural language processing (NLP) as the primary interface for accessing data, thus bringing data to new classes of users — ones who previously may not have used BI.
While BI is already key tool in improving CX, boosting productivity and increasing efficiencies, it is only going to become more so as we move forward.
The future of business intelligence is likely to be much more automated and aggressively utilised, thanks to fewer bottlenecks in terms of interface limitations and the free flow of data.
In addition, it appears likely that in the future, BI will also be capable of thoroughly integrating with big data solutions. This only makes sense, as BI and big data generally have common goals, such as serving data-driven decision-making.
BI in the near future will also be in a position to properly leverage the potential of artificial intelligence and machine learning solutions. The net result of this and the integration with big data should include the delivery of valuable information and insights at a much more rapid pace, which in turn will lead to time-savings, cost reductions and ultimately, increased profitability.
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