Data security consistently tops the laundry list of security priorities because it must. Organizations are collecting data, creating data, using data, and storing data in some way or another. Mishandle data or disregard privacy, and you’ve got a public relations fiasco on your hands with the potential to disrupt business operations or hurt the bottom line.
So, we know that data security is a priority, but what does that mean? What are organizations actually doing here? How much are they spending, and where are they focusing their efforts? And what are they doing about privacy? I’ve dug into data from Forrester’s Forrsights Security Survey, Q2 2012 and data from the International Association of Privacy Professionals (IAPP) to answer these questions in a newly published benchmarks report for our Data Security and Privacy playbook. Note: This is not a shopping list, nor a check list, nor is it a “spend x% on data security because your peers are doing so!” manifesto. This report is meant to be a starting point for discussion for S&R pros within their organizations to take a closer look at their own data security and privacy strategy.
I spent a jam-packed day with security software and services provider AVG last week, checking out their 2013 product line-up for free antivirus and paid premium products, and participating in roundtable discussions with press, analysts, and AVG executives about consumer security, mobile, privacy and policy. Here are my reactions to what AVG is doing:
LIKE: Consumer data (yes, I’m biased here, being the data nerd). AVG has lots of it and it’s all free. This is awesome because it’s a great resource not just for the industry but for other parties to use in education and awareness program design. They’ve done studies across 11 countries for their Digital Diaries studies, surveying parents and kids of different age brackets from 0 to 17 to understand online behaviors and attitudes. Here’s a data nugget that caught my attention: by the time they are two years old, 81% of children have some kind of digital footprint (online photographs, personal data, email and/or social networking accounts). 81%!
If you think the term "Big Data" is wishy washy waste, then you are not alone. Many struggle to find a definition of Big Data that is anything more than awe-inspiring hugeness. But Big Data is real if you have an actionable definition that you can use to answer the question: "Does my organization have Big Data?" Proposed is a definition that takes into account both the measure of data and the activities performed with the data. Be sure to scroll down to calculate your Big Data Score.
Big Data Can Be Measured
Big Data exhibits extremity across one or many of these three alliterate measures:
At IBM's Smarter Analytics event this week, clients and partners presented success stories about how organizations are driving business value out of big data, analytics, and IBM Watson technology.
- City of Dublin, Ireland using thousands of data points from local transportation and traffic signals to optimize public transit and deliver information to riders.
- Seton Healthcare mining through vast amounts of unstructured data captured in notes and dictation to get a more complete view of patients. Seton currently uses this information to construct programs that target treatments to the right patients with a goal of minimizing hospitalizations in the way that most efficiently optimizes costs with benefits. The ability to mine unstructured data gives a much more complete view of patients, including factors such as their support system, their ability to have transportation to and from appointments, and whether or not they have a primary care physician.
- WellPoint using Watson technology to improve real-time decision-making by mining through millions of pages of medical information while doctors and nurses are face-to-face with patients.
But, clients warned that as much as the technology is advancing, the biggest hurdles remained the internal ones. Clients stressed that they face a critical challenge in introducing, driving, and changing the organizational mindset to work in a new way that can take advantage of these great advances in technology. What did they suggest?
1) Executive sponsorship from the top (C-level)
2) Hiring or retraining for new roles like data scientists (schools like Syracuse are introducing and promoting new programs out of their iSchool, which can help with reskilling experienced talent from other areas)
Join us at Forrester’s CIO Forum in Las Vegas on May 3 and 4 for “The New Age Of Business Intelligence.”
The amount of data is growing at tremendous speed — inside and outside of companies’ firewalls. Last year we did hit approximately 1 zettabyte (1 trillion gigabytes) of data in the public Web, and the speed by which new data is created continues to accelerate, including unstructured data in the form of text, semistructured data from M2M communication, and structured data in transactional business applications.
Fortunately, our technical capabilities to collect, store, analyze, and distribute data have also been growing at a tremendous speed. Reports that used to run for many hours now complete within seconds using new solutions like SAP’s HANA or other tailored appliances. Suddenly, a whole new world of data has become available to the CIO and his business peers, and the question is no longer if companies should expand their data/information management footprint and capabilities but rather how and where to start with. Forrester’s recent Strategic Planning Forrsights For CIOs data shows that 42% of all companies are planning an information/data project in 2012, more than for any other application segment — including collaboration tools, CRM, or ERP.
One of the reasons I enjoy working at Forrester is the unique opportunity to turn data into actionable insights that tech marketers can use to drive more revenue for their companies by increasing the efficiency and effectiveness of their marketing.
Based on this data and our work with clients, five simple but powerful guiding principles have emerged around targeting, marketing vehicles, content strategy, and messaging that all tech marketers can apply. Over the next five weeks, I’ll be sharing them with you via this blog, one per week on Tuesday mornings, starting today.
Guiding Principle Number One: Targeting
We all know that high-consideration technology purchases at medium and large enterprises involve multiple stakeholders. However, all too often, marketers and/or sales associate a disproportionate amount of influence to one or two particular influencers; for example, the CIO or line of business (LOB) professional. The reality is that no one influencer has more than 30% of the total power through the purchase process. You must ensure that you are allocating your marketing programs proportionally across all of the appropriate influencers and that you don’t get fixated on simply engaging one or two influencers, thinking that they control all of the necessary power.
So, the next time you are deciding whom to target, remember the 30% rule — it will serve you well.