Have a plan B. AT&T Wireless’s Siebel system upgrade involved vastly complex systems integration and testing that pushed up against, and crashed through, an immovable deadline: wireless number portability. An alternate means for accessing customer data or a plan to be able to roll back to the earlier, more stable version, if necessary, would have saved the company millions. Keep testing requirements strong-even when projects fall behind. When projects run late, testing always suffers, with often disastrous results.Reduce integration wherever possible. When all of AT&T Wireless’s major competitors chose another company for wireless number porting, AT&T Wireless should have rethought its choice of a competing vendor, which meant extra layers of integration that ultimately failed.Postpone layoffs and offshore outsourcing until a vital systems project is completed. Morale and productivity among the AT&T Wireless IT staff were shattered by rumors of offshore outsourcing and layoffs that swirled around the project but were left mostly unaddressed by IT leaders. Keep the communication lines open and clear. If layoffs or outsourcing is unavoidable during a project, communicate that news clearly and get the changes over with as early in the project as possible. -C.K. Related content brandpost The steep cost of a poor data management strategy Without a data management strategy, organizations stall digital progress, often putting their business trajectory at risk. Here’s how to move forward. By Jay Limbasiya, Global AI, Analytics, & Data Management Business Development, Unstructured Data Solutions, Dell Technologies Jun 09, 2023 6 mins Data Management feature How Capital One delivers data governance at scale With hundreds of petabytes of data in operation, the bank has adopted a hybrid model and a ‘sloped governance’ framework to ensure its lines of business get the data they need in real-time. By Thor Olavsrud Jun 09, 2023 6 mins Data Governance Data Management feature Assessing the business risk of AI bias The lengths to which AI can be biased are still being understood. The potential damage is, therefore, a big priority as companies increasingly use various AI tools for decision-making. By Karin Lindstrom Jun 09, 2023 4 mins CIO Artificial Intelligence IT Leadership brandpost Rebalancing through Recalibration: CIOs Operationalizing Pandemic-era Innovation By Kamal Nath, CEO, Sify Technologies Jun 08, 2023 6 mins CIO Digital Transformation Podcasts Videos Resources Events SUBSCRIBE TO OUR NEWSLETTER From our editors straight to your inbox Get started by entering your email address below. Please enter a valid email address Subscribe