Our friend Paul Bentz at CISQ recently published an article detailing the imperative for CIOs to become digital leaders. Research from Gartner confirms that high-performing CIOs are leaders because of their participation in a digital ecosystem. To effectively drive transformational programs, CIOs must have a keen understanding of how digital drives both business and IT success.
CAST recently participated in a TechMarketView round table in London, discussing the effectiveness of digital strategies in banking. It’s no surprise that banks are facing some significant headwinds heading into 2017, including geo-political uncertainties, increased regulation, the need to modernize legacy systems and growing cyber threats.
Digital is no longer “just another channel” – it’s essential to success and securing optimal position for the next generation of banking customers. In order to capitalize on opportunities, bank management must establish solid KPIs to create and sustain the right behaviors in a digital environment.
This fall, CAST hosted its first Seminar on Productivity Measurement in the Context of IT Transformation featuring representatives from the retail, banking and insurance industries in the Netherlands. Featured speakers included CISQ, Allianz, BNP Paribas and METRI.
Productivity measurement is particularly useful for individuals who lead enterprise governance and measurement programs, in addition to practitioners working on business-critical software. Pragmatic approaches to automated software measurement are more important than ever, especially as the shift to digital continues.
The key to security is to ensure that your most sensitive data is handled with proper controls in place. This should include working with your architects to explore the architecture of applications that handle the most critical data, starting from the data elements themselves and fanning out via impact diagrams (for example, CAST does this with the Application Intelligence Platform). Over time, your team will be able to establish secure architecture components that should handle all sensitive data.
In software maintenance and evolution, it is important to assess both code health and application architecture in order to identify issues impeding software quality goals. One way to move the needle toward software quality is to use Technical Debt (TD) indexing as a method to evaluate development projects.
We recently presented a paper at MTD 2016, the International Workshop on Managing Technical Debt put on by the Software Engineering Institute at Carnegie Mellon, where we discussed the way five different and widely known tools used to compute Technical Debt Indexes (TDI), for example numbers synthesizing the overall quality and/or TD of an analyzed project.
It seems more and more frequently we see security and cyber-attacks in the news today. From Yahoo’s apparent cover up of a massive security breach that is damaging its merger with Verizon to the even more recent bank hack in India, where millions of debit cards were compromised, it’s apparent that there are holes in our current defense systems. Adding to the complexity of it all, eWeek has reported that DDoS attacks hit record highs in Q3 2016.
For most data-intensive organizations, it would spell disaster if mission-critical or customer information was leaked. What’s more, security gaps are known to go undetected for much longer in enterprises with a high percentage of legacy systems.
Insurance organizations have reached a tipping point. Historic institutions, with in some cases hundreds of years of service, they are being forced to transform due to changing consumer demands and nimble, technology-centric startups bringing innovative products to market. No stranger to regulatory and privacy concerns, Insurance carriers have overcome many roadblocks throughout their lifetime of doing business. Now they must tackle their legacy IT systems and improve software risk management to deliver the value today’s market is after.