Big Data's impact on the CIO role
- 24 May, 2012 22:00
Most CIOs today are working hard to align IT capabilities to business goals. Their line-of-business peers are asking for increased accuracy of data and insight delivered in near real-time, critically, while the customer is actually interacting with the company.
Big Data is putting more pressure on budgets but it also raises the question of whether CIOs have the capabilities to generate value in a consumer-educated world.
Some examples of how the power of Big Data can be harnessed include:
Marketing managers making offers based on an understanding of static history and then using the context of the current situation and interaction to make a more relevant offer.
Chief risk officers are looking to prevent fraud in real-time to reduce detection costs and improve customer experience.
Companies are trying to obtain a better understanding of consumer needs through improved knowledge of customer life stage and behaviour. They are achieving this by analysing social and online data and then combining that with their existing CRM and transactional data.
Operational managers are looking to improve the way they reschedule resources and meet customer expectations, particularly in the light of unforeseen events.
The top five Big Data challenges facing CIOs are:
Data governance, specifically the need to automate the way data is martialled and transformed from data entry through to insight and action. CIOs understand that data itself is cheap; mining it is expensive and time-restrained businesses need to optimise the data supply chain.
Data quality. Public sector CIOs especially recognise a move towards evidence-based policy. This means data must be trusted and reliable. With so many different applications and customer touch points how do we ensure quality?
Performance requirements of the business. The problem is not just shortening a one-off time-to-delivery but in making sure insight can be delivered regularly in shorter intervals.
Getting a single view of customers, assets, products, vendors or employees. The difficulty is that customer information is strewn across different lines of business with differing details.
The difficulty of managing and harnessing value from unstructured data . While some have experimented with open source software such as Hadoop, it’s rare that they’ve been able to successfully implement business value.
Three themes consistently pop up as keys to success for customers using Hadoop:
Alignment to line of business goals. Alignment of the technology to a business KPI is moving it out the laboratories and into the day-to-day operations creating sustained value. For example increased response to marketing campaigns or improved accuracy of fraud modeling, detection and prevention.
End-to-end data management. Storing the data is one aspect of delivering value. You need a data process factory to manage the collection, transformation and loading of data to Hadoop. The key is to then ensure the data can generate insight. This requires analytics to sift, filter, aggregate existing data and analyse to produce insights.
Power of aggregated insight of structured and unstructured data - The need to combine unstructured data from IVR [interactive voice response], social, online and email with internal CRM, ERP and transactional systems. An example is looking at how marketing departments are improving accuracy and personalisation of offers based on increased knowledge of customer behaviour, lifestyle, influence and sentiment.
Making better decisions in a data-rich world relies on increasing the ability to deliver more timely, reliable, trusted and accurate data. Data governance, data quality, master data management and data integration are the key to unlocking sustainable value from business analytics.
The author is the product marketing manager for Southeast Asia at business analytics and software services company SAS. He is based in Sydney. Reach him at firstname.lastname@example.org and Twittter:@vcotte
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