In a time of challenged economies and increased competition, organisations are under tremendous pressure to find new ways to drive revenues and profits. They turn to their traditional business assets to address these challenges – financial investments and people. But, most enterprises are sitting on a third viable asset that may be a hidden goldmine– the data goldmine.
Essentially, you can monetise your data in two ways: by using it to make money and by using it to save money
By most definitions, true “data monetisation” is focused on the delivery of data as a direct revenue generating asset. Making data marketable and data monetisation is essentially the process of realising the significant financial value locked away in your enterprise. Organisations in many industries are finding that information and analytics are becoming their newest products. Those that have become confident about the value and quality of their data may even begin to compete with the traditional market data providers from whom they have purchased data historically. While the potential to “monetise” data has always existed, the proliferation of “big data” from new sources such as mobile, social media, machines, location devices and the cloud is presenting new opportunities, as well as challenges, to make information an integral part of your organisation's value proposition. And, importantly, this information can be made marketable to attract and engage more with your customers.
Expanding the definition, another essential approach to monetising data is to leverage it internally to drive quantifiable performance gains and cost reductions. Customer data can help sales and marketing teams find ways to reduce customer churn through the analysis of purchase history and buyer behaviours to better target and engage with customers with more personalised merchandising and promotional campaigns. Today’s visual analytic tools are helping business analysts generate better insight. But generating insight is only part of the equation. The greater opportunity for return on data investments comes from operationalising insights. This is achieved by delivering operational decision-making and comparative performance metrics to everyone in your organisation through easy-to-use, self-service analytic apps. Empowering stakeholders to tap into real-time company information allows them to better serve the customer, which in turn drives loyalty and revenue.
Business intelligence (BI) and analytics are often applied to cost control activities. Operationalising insights can drive extreme cost cutting throughout operations, customer care and the supply chain. This is true when provided to employees and business partners alike. Greater transparency and availability of information, metrics and analytics changes behavior and creates a culture of accountability. The results are dramatic decline in waste, abuse and even fraudulent activity.
But, what do businesses need to be successful? Here are the three key ingredients:
1 – Integration: Data management for analytics now requires timely availability of information from a multitude of sources. The latency of required data is commonly becoming real-time or near real-time. The sources of data may reside in ERP, CRM or legacy systems inside the enterprise, as well in the cloud and even public domain. Many organisations are finding that their data takes on much greater value when correlated with industry data. This is creating new opportunities for data monetisation. Advanced analytics such as predictive models often require many variables from various data sources in order to produce the most accurate outcomes. When predicting potential crime, for example, historical data needs to be applied to the model along with current factors such as population, traffic, weather, and events in order to deliver the most accurate results.
2 – Integrity: Decisions need to be made based on accurate data. If your data will be made available to external stakeholders and customers, accuracy is critical. This is often the roadblock which hinders organisations from moving forward with their data monetisation goals. Data integrity concerns include data quality, data consistency and security. Data quality challenges are being uncovered at every turn. There are simply greater volumes of data from more sources being analysed by more individuals. Data shared with third parties, such as processing firms, tends to generate higher degrees of inaccuracies and incompleteness. Data quality is often addressed tactically with isolated sources of data. These are often temporary remedies which fail to treat the symptom versus the cure. Master data management (MDM) takes a more strategic approach to solving data integrity by making sure that data is validated across all operational and analytical sources of data. Data governance will ensure that inadequate processes are addressed through collaboration between business stewards and IT staff. Delivery of data outside the firewall requires the strictest of data security efforts as well as the hardening of applications and vulnerability threats.
3 – Intelligence: Assume everyone is a decision maker throughout the organisation, throughout the partner ecosystem and throughout the potential customer base. Different stakeholders need to access and interact with data in different ways. They will also possess a wide variance in technical skills and understanding of data.
Be sure to choose a business intelligence (BI) and analytics platform that offers:
- Dashboards and scorecards for executives in the c-suite
- Advanced tools for analysts, such as data visualisation and predictive analytics
- Highly interactive, self-service analytical apps for the non-analyst. Most employees, partners and customers will be unable to utilise analytic tools, but they want more than a static document or dashboard. An interactive, intuitive app approach works best for these information consumers.
- Mobile BI and analytics to provide easy access to information via smartphones and tablets for remote tasks. Mobile solutions should automatically support all devices and operating systems.
The right BI and analytics platform deployed with a progressive agile strategy will allow every stakeholder and marketing executive to recognise immediate value. When executed well, the entire organisation will benefit.
By Michael Corcoran, SVP & CMO at Information Builders.
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