For business decision-makers to leverage big data as a means of improving customer engagement for their organizations, they must first focus on the challenges that big data presents, and then take key roles in leading big data initiatives (following best practices) to derive their full value. These points are the foundation for the latest report from Forrester, “The Big Deal About Big Data For Customer Engagement”. This blog will highlight some of its key findings and conclusions.
Organizations are moving away from siloed transaction-oriented systems – such as enterprise resource planning (ERP), customer relationship management (CRM), and dealer management systems – and toward more integrated and socially aware systems. They then need to manage the surge in the type and overall volume of data, and to analyze a large amount of complex data in real time.
CIOs are facing an onslaught of unstructured data from multiple sources, like social platforms and semistructured data from machine-to-machine (M2M) communication. This signifies the need for traditional business intelligence (BI) approaches to supplement big data approaches, even for basic structured transactions. Forrester defines big data as: Techniques and technologies that make handling data at extreme scale affordable.
Where BI Consulting Firms like Perficient play a role is that Big Data is about having the technology and people with the appropriate analysis skills. This allows firms to make sense of huge volumes of data (often semi-structured or not structured at all) in an affordable manner, and to be able to invest in new capabilities and approaches to collecting, storing, analyzing, and distributing data:
- Online platforms and communities such as Facebook, LinkedIn, and Twitter generate large volumes of unstructured data. Companies are taking advantage of social media’s growing user base, using tools like Facebook, LinkedIn, and Twitter to engage with customers directly. This helps firms undertake sentiment analysis on their consumers and better tailor their market outreach programs.
- Data from mobile devices, self-service kiosks and smart cards help organizations better understand consumers.
- Intelligent systems transmit semistructured data that help drive operational improvements. Through the use of RFID (radio frequency identification) and sensor networks, semistructured data can be transmitted to make better business decisions.
While leveraging data analysis to optimize customer engagement is not a new concept, it has been greatly enhanced through new models and metrics for analyzing many more types of data. Sophisticated predictive models based on real-time data streams help firms better understand and measure their engagement with customers, and can often unlock new revenue streams, and overtake competitors.
Big data is often painted as a topic only relevant to consumer-facing industries like retail and telecom, but even organizations like manufacturing and government, that do not deal with consumers, are realizing the impact that big data is likely to have on their business decisions.
Companies are now facing an explosion of information, both from traditional data and big data. This means that IT teams are often unable to respond quickly enough to new market dynamics and improve customer experiences. Firms are struggling to manage a new set of challenges around the type, complexity, and volume of data.
The Future of Big Data
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Forrester has concluded that there are now 5 “V”s that companies need to be aware of: volume, velocity, variety, variability, and value — when considering big data. Other conclusions:
- CIOs are using multiple pproaches to tackle big data.
- Best practices for big data are poorly defined.
- Involving business leaders in big data implementations is an ongoing challenge.
- Managing big data requires changing existing information strategies.
Forrester believes that IT decision-makers must expand their BI focus to fully support unstructured and semistructured data as a key requirement for enabling and supporting improved customer engagement. While structured data remains critical to decision-making, it is unstructured data will help drive the customer engagement process. Early awareness of the need to support unstructured data has been most acute in customer-facing organizations, especially those requiring critical response times, like hospitals and hospitality.
Netezza, SAP HANA, Vertica, and many others are now making it viable to store and process massive amounts of data in a matter of seconds. Open source options are also increasingly enterprise-ready; it is commonplace to hear names like Hadoop, HBase, Avro, Pig, ZooKeeper, Apache Commons, and Lucene during big data discussions.
Forrester believes that the need to process different big data types requires organizations to adopt different technologies. Among these would be: 1) infrastructure services based on virtual commodity hardware and workload management; 2) horizontally scalable, distributed data management services and distributed processing; and 3) analysis optimized for operations in the cloud.
It also believes in the following architecture categories: 1) real-time scenarios heavily based on complex event processing; 2) parallel processing/fast loading, typically based on Hadoop; and 3) high-performance query architectures based on in-memory or appliance architectures. Depending on the business need, organizations must then define the most relevant technology architecture and choose tools. In many cases, organizations can combine multiple architectures.
Big data initiatives require organizations to take a holistic approach and bring together both business and IT leaders to stitch all of the pieces together.
- Step 1: Centralize and redefine the data-gathering process. Forrester believes that companies must view big data implementation as a business project, not as an IT project.
- Step 2: Better manage customer profiles.
- Step 3: Optimize the data warehouse environment.
- Step 4: Invest in analytical models and forecasting to better serve the business.
- Step 5: Keep information relevant to employees by using visualization tools.
Forrester recommends that CIOs should use the following approaches to get the most out of their big data initiatives:
- While IT and business need to work together, the business must own the initiatives.
- Change the information management strategy to accommodate new data sources and types.
- Start small, avoid silos, and incrementally roll out big data initiatives. The key is to start small, reuse components of the existing infrastructure, and solve the selected use cases. This will help a firm better manage the initiative, avoid silos, and measure success on an ongoing basis.
Vendors are finding increasing opportunities globally to undertake big data POCs. Forrester believes that, while vendors will continue to witness increasing traction for big data over the next two to three years, the key to driving incremental revenue and growth will be to link business metrics and outcomes directly to big data projects. The challenge will be to engage the business leaders in the prospective organizations who are either not aware of big data or don’t know enough about it to see its direct link with business outcomes — customer engagement in particular.
More in depth information, including many examples and scenarios of the above, can be found in the source for this blog: The Forrester Report, “The Big Deal About Big Data For Customer Engagement” by Sanchit Gogia.
