After debunking the myth that big data is just for the big end of town I set out on the road to listen to what is happening locally. For the past two weeks I have met with over 50 Chief Information Officers (CIOs) around Australia and Asia discussing their 2012/13 priorities. I thought it would be useful to hear about the specific goals and challenges facing them as they move from a mindset of keeping the lights on to that of a strategic seat at the boardroom table. It was very refreshing to see that the CIO was working hard to align IT capabilities to business goals. A quote from Gartner has certainly sparked some action in CIOs. The quote discusses the moving trend in Chief Marketing Officers to spend more on IT - predicted to surpass CIO spending by 2017.
Their line of business peers are asking for an increase in the trustworthiness of insight, increased accuracy of data, insight delivered in near real-time, and critically, delivered when the customer is interacting with company. The big data hype is applying even more pressure to costs but also asking questions as to whether CIOs have the new capabilities to derive value in a consumer-educated world.
Some examples of what the specific lines of business were trying to achieve are:
- Marketing arm of an insurance company looking to make offers based upon understanding of static history and then using context of current situation and interaction to make a more relevant offer.
- Risk officer of a bank looking to prevent fraud in real-time to reduce costs in detection and investigation.
- Chief financial officer of a gaming company asking how to deliver a more personalised experience to punters based on history and current playing habits.
- Head of marketing for a telecommunications company looking to obtain a better understanding of consumer needs by analysing social and online data and then combining that with their existing CRM and transactional data.
- Chief operating officer of a transport and logistics company looking to improve the way it reschedules resources, freight and customer expectation based on unforeseen events like the tsunami in Japan.
Here are the top five challenges facing CIOs in trying to deliver to these business goals:
- Top of the list is data governance. Specifically the need to automate the way data is martialled and transformed from data entry through to insight and action. As one CIO put it, “Data is cheap. Mining the data is expensive and timely. We need to optimise the data supply chain”
- Secondly, data quality is back on the table. A government CIO remarked, “a move towards evidence based policy means data must be trusted and reliable, thus bringing into scrutiny the quality of the data”. With all the different applications and citizen or customer touch points how do we ensure quality?
- Close third is an inability to meet performance requirements of the business with the existing platform approach. Interestingly the problem was not just in shortening a one-off time-to-delivery but in making sure insight could be delivered regularly in shorter intervals.
- Fourth is an old chestnut - single customer view, asset, product, vendor or employee. The difficulty is that the customer is strewn across different lines of business with differing details. A retail bank CIO gave an example of why it is important. “We have a customer; Maryanne Smith for a credit card, Mary Smith for personal loan, and Joe and Mary Smith for home insurance. Currently the bank are marketing to approximately 20 million individuals when it’s clear we only have around 5 million unique customers. There is a lot of needless cost and effort spent on irrelevant marketing offers with low response rates. Haven’t we all experienced that? So what does that mean to customer experience and churn?”
- Fifth is the inability to manage and harness value from unstructured data. While some had experimented with Hadoop none of them had successfully implemented value.
If this sounds like you, then take comfort in knowing there are options out there. It was clear that making better decisions relied upon increasing the ability to deliver more timely, reliable, trusted and accurate data. While we have been recently discussing the power of high performance analytics it is clear that data governance, data quality, master data management and data integration are seen as the key to unlocking sustainable value from business analytics.
We've got more to come as we go explore examples of how local companies are addressing these issues to drive value from big data. In the meantime let us know how your how your data governance initiatives have delivered value.