Online transactions make up less than 1% of the overall retail market in South Africa according to Enst & Young. Although this is extremely low when compared with the UK, where online shopping constitutes 14% of retail sector purchases, this number is escalating at an impressive year-on-year rate according to latest MasterCard Worldwide Online Shopping Survey.
I just returned from a meeting with one of my clients, a major player in the automotive industry, who has an integration between SAP R/3 and Salesforce. Every day they send flat file extracts from both systems to an external agency to perform data matching. This got me thinking, why not add a small data quality, or customer data management, component into your integration workflow, to do this automatically rather than going to an external agency?
I’ve previously stressed the business value of data and process integration, not only for improving process efficiency but also to enable enterprise mobility. However, I’d like to explain why data quality and Master Data Management is a key component of any data integration or enterprise mobility project.
With 25% of companies believing their data is inaccurate, 91% suffering from common data quality issues, and up to 12% of revenue being wasted just because of poor data quality, this looks like a small step that can have a significant impact on the business.
Recently I’ve been thinking about a trend in mobile apps, which seem to be moving away from the “user interface (UI) first” approach that has dominated websites and mobile apps to date. Rather, it seems that advancing technologies are making the UI subordinate to an overall user experience (UX) which includes not only the graphical interface but also the back end connectivity, performance and reliability. Further, between improving voice input, haptic feedback and small, wearable devices, the screen is becoming a less significant part of how we interact with mobile apps.
I believe there is a very interesting intersection between how we will use mobile apps and how we will develop them in the future: apps will become more about actionable notifications than destinations; and we will develop them using pre-written components as much as possible rather than custom coding.
I recently wrote about my experiences with Google Glass, a device I've had for a few months now. For all the potential applications the device has, I find that the one I use most is Google Now, which isn't a traditional mobile app at all. Google Now runs mostly in the background, keeping track of my calendar, location, local traffic and so on, and just pops up occasionally to keep me aware of what I need to do.
I also recently watched the launch of the new Moto X, and was fascinated that it has a voice co-processor (like the M7 and M8 motion co-processors in the iPhone 5S and 6) which uses very little battery and is always on, always listening, allowing you to communicate with your phone without pressing buttons. Add a Bluetooth headset and you greatly increase the range at which you can communicate with your phone... and of course a smartwatch could also use this. Between Glass and Google Now, Moto X and its chip, and the Internet of Things I think we can start to see where the future is going.
Big Data is one of the most widely-hyped buzzwords of the tech industry, and that means there is a lot of hype and misunderstanding. Worse, concepts like “data science” are constantly thrown around, making this emergent technology appear like black magic to the business leaders who could benefit from it. This post aims to cut through the hype to help you understand what Big Data is and its relevance to your business.
This year I have worked with my customers on several business intelligence (BI) projects, and from what I have seen, the key to making these systems effective for the business is to go further than they allow on their own.
Business intelligence systems are excellent at presenting information in a way that lets the user make informed decisions, but you unlock far more business value by making the data actionable, allowing the user to kick off business processes based on the information. This turns business intelligence from a dashboard into a control panel for the business.