When I think of companies changing their culture with technology, I often think of how similar the efforts are to hip-hop culture. Hip-hop artists like the iconic Rakim evolve to stay relevant to faithful fans and to sometimes reconnect to their musical roots.
The quoted lyric, a reflection of the five years that had passed since he last recorded with partner Eric B, is from a solo album noted by music critics as Rakim’s evolution from his now-legendary work.
One corporate culture, that of iconic General Electric, is undergoing a transformation to stay relevant to its faithful customers and reconnect to its innovation roots. CEO Jeff Immelt announced in a Linked In post that all GE new hires will learn programming to inject a startup attitude in. Immelt writes, “It doesn’t matter whether you are in sales, finance, or operations. You may not end up being a programmer, but you will know how to code.”
Is an emphasis on learning technology necessary? Immelt’s directive is certainly a response to the Internet of Things movement that networks disparate devices and overhauls business models seamlessly overnight. GE is not alone in that commitment as every company face adjusting their business model to accommodate the Internet of Things era.
But is an emphasis on making business professionals understand technology masking a need for understanding management frameworks that mesh digital and real-world concerns?
In a word, yes. Management frameworks are key to implementing the technology successfully. They also hold implied opportunities for savvy analytics planning as well.
Take waterfall development, a typical methodology for projects where tasks are conducted sequentially. Some developers feel using waterfall development leads to static requirements and line-in-the-sand budgets, ultimately giving no room to iterate programming features into a favorable design. Changes are complex to complete after the work is done.
Developers have begun to adopt agile development, an umbrella term for incremental improvement practices. The iterative nature of agile development better aligns development tasks to changing programming requirements. It is made to make software sustainable in a production environment, in which betas are issued prior to a full rollout. In an IoT age where devices are becoming programmable, developers are finding agile development an asset to device creation as well as software issues.
Management frameworks included with agile development techniques offer advantages well beyond a manager’s increased familiarity with a technology. Managers can make better estimations of analytic technical challenges -- from metric selection to advanced data modeling -- because the code reviewing that support agile development surfaces quality issues as programming details are iterated. Establishing accurate analytics is inherent in development.
For example, imagine managers recognizing overfitting in their models. Overfitting is a statistical predictive model that describes random error or noise instead of the underlying relationship being sought from the data. Managers must have acumen to know when they are facing poor decisions based on modeling iterations that has gone awry.
The continuous integration of programming features in agile development allows managers the right reflection moments to verify that intended metrics and analytic reporting align with the context of the data sources. Those reflections lead to better upfront communication with the team on what programmatic analytics activity should be included. Letting a team know the influences on measure objectives is prevents needless complexity, a hallmark benefit of agile development.
The benefits extend to other tech offerings, such as IoT-as-a-Service and Analytics-as-a-Service. These services reveal how resources in a cloud or IoT environment are consumed in different ways over real time. The analytics reports on these services can inspire managers to understand how to upgrade devices or how to service customers between software upgrades.
Immelt was right when he wrote that culture “is not just apps. It’s a combination of technology and people.” Vetting management methodologies against technology development is the best way of ensuring that one’s working culture remains alert to analytic practices that ultimately serve customers well.
What management methods and processes have you experienced that have helped managers apply analytics effectively?