Editor’s Note: Continuing with our Crystal Ball 2012 blogs, Michael Iseyemi, our Global Chief Security and Risk Officer, provides his insights on how the future of data collection and analytics will reshape the way companies do business.
RISK MANAGEMENT IN THE NEW NORMAL
Intense competition, economic uncertainty, credit and commercial market shift, disruptive technologies, and regulatory changes are all affecting decisions regarding what to outsource and what to retain in house. Service providers need to align with client CEO/CFO requirements towards mitigation of these risks by creating new, enhanced partnership approaches.
|Data analytics and data privacy can coexist
Risk management is crucial and has to be proactive and relevant to the realities of the new marketplace. A March 2012 risk in review document
by PwC cautions that alignment with new market realities will require greater understanding and risk management. According to that study, economic uncertainty, competition, regulatory compliance, and data privacy and security are among the top 10 risk management considerations
. With increased financial insecurity in global markets, it found that 60% of executives see regulatory compliance as a great concern.
As such, it is important to take a proactive approach to ensuring proper level of risk mitigation to address new market realities and ensure solutions provided meet or exceed expectations, align to executive objectives and markets and increase wallet share.
Today, data equity and brand equity go hand in hand. Aggregating business data and mining the wealth of information they contain can enable organizations to gain better visibility into trends in their businesses and acquire business intelligence. Data analytics helps you make informed decisions in real-time and, when driven by business objectives, help increase wallet share. However, we need to be ever mindful of regulatory requirements and risk mitigation factors.
OUTSOURCING DATA & ANALYTICS: A NON-TRADITIONAL PERSPECTIVE
With data feeds from multiple sources and the need to co-mingle structured and unstructured data content including social media, Web properties, and others, how do you aggregate and analyze this Big Data, construct a data analytics methodology and allocate resources to gain the most value? This is where the right partner can make a big difference by providing a business model that will maximize value creation.
For this reason, outsourcing of data analytics is entering the mainstream as part of a larger evolving trend, whereby businesses are seeking cloud-based solutions, third party data analytics tools and consultation—to manage data content from multiple sources and make sense of that information to drive the best business decisions. Ultimately, businesses need to think about data from a non-traditional perspective given connectivity to social media, mobile devices, virtual environments, and cloud computing platforms.
Businesses are looking to data analytics solutions to examine trends and understand commonalities and complaints. The end goal is to leverage the information that data analytics provides to enhance Voice of the Customer (VOC), prevent escalation of issues, drive revenue, enhance market share, and create efficiencies. Ensuring these goals, regulatory compliance along with data privacy, will require a balanced approach.
The ability to aggregate customer data will help you better understand the buying ecosystem including the expectations of current and potential customers. Combining this intelligence with chat platforms and co-browsing capabilities (linked to social media) can provide assistance in purchase decision making translating to increased sales and enhanced customer relationship management.
For one client in the healthcare space, we designed a speech analytics program using keywords to identify issues with agent training. These keywords and phrases (e.g., “I’m sorry but…”) help coaches work with agents to improve specific problem areas, especially handle time and first call resolution. We have also been able to identify trends over time—helping us effectively modify our recursive training and new hire curriculum to ensure our agents are equipped to provide the best possible customer experience.
When done right, data analytics should support predictive modeling, and identify current and future sales trends, business risks and revenue/profit opportunities. Ultimately, data should support business decisions in a holistic manner.
THE DATA PRIVACY CONUNDRUM
Data privacy considerations must remain paramount. While they can be impediments to accumulating data, if privacy considerations are well understood and accommodated, they can actually be leveraged to maximize value creation in support of your business goals and objectives. Rather than avoiding privacy considerations, seek to understand and embrace them and then design solutions accordingly.
In my experience, the best way to address the data ownership issue is to place more control in the hands of the data owners and let them make decisions about how much of their own information they’re willing to provide and share. The general public is more intuitive and intelligent than businesses often give them credit for. In most cases they will provide information, but will want the consideration of being asked first in addition to being given the perception that they maintain control of their information.
Data collected without consent may lead to public backlash as we’ve seen with Facebook, specifically with recent reports that a class-action lawsuit was filed against it for allegedly tracking users who ventured off its online social network.
Alternatively, when control is placed in the data subjects’ hands, they decide what services they want, and their input leads to better service customization. This clearly is a win-win for both parties.
When data is collected, it needs to be properly and securely stored. Data strings can “anonymize” data and prevent personal data from falling into the wrong hands. Encryption is also very important in preventing data leakage. Always be mindful of the design and architecture of databases in terms of access, storage, transport and linkages.
Data collection and storage procedures must adhere to the appropriate regulatory requirements, and this is where it becomes crucial to follow a standardized approach. For example, service providers may work in multiple verticals with a plethora of standards in banking and healthcare. This, combined with a global footprint both with respect to delivery of services and markets served, makes data protection and adherence to regulatory requirements even more challenging. Emerging markets, such as India, are beginning to adopt stricter data privacy rules and requirements and the bar is continually being raised world wide. A regulatory management best practice is to standardize by first understanding commonalities. From there, we can infer a significant level of common standards and requirements, while identifying the special considerations associated with each directive and the safe harbor requirements in different jurisdictions.
What’s your experience with data collection and data privacy? What’s your comfort level with trusting customer data to an outsourcing services provider?