Advanced Technology- Advanced technology has implications that can transform a company’s very nature – from operations, to how people behave, to why leadership makes the decisions they do.
However, the technology’s impact is limiting and potentially damaging if the business doesn’t understand how to apply it strategically.
It’s hard not to get caught up in the excitement of adopting AI and other new technologies that have game-changing potential for the future of the business. The hype sometimes prompts companies to jump in too fast for the wrong reasons, wasting time and money on technology solutions that are not tied directly and intently to the goals and vision of the business.
New technologies should never drive the adoption of a new business model or strategy; just the opposite, the business strategy must drive the adoption of new technologies.
The problem with chasing the shiny new object is that it puts an emphasis on quick wins rather than sustainable results. This is one of the biggest threats to a transformative culture, and it causes companies to ultimately miss the exponential, transformative benefits of connecting digital technologies like AI, blockchain and cyber into an integrated architecture.
And while these technologies of course help with day-to-day functionality, they won’t have long-lasting value if they don’t find their way into broader business strategy.
Instead of racing to adopt the latest technology, businesses first need to adopt a top-down approach that looks at the business model first, and then acquires the capabilities, skillsets and people needed to create that change. In doing so, businesses greatly reduce the risk of making heavy investments in technology solutions that later need to be completely rebuilt. It’s taking a step back to look at the “why” and “how”, instead of just the “what.”
So, what does this strategic implementation actually entail?
It all goes back to data. The bottom line is that most organizations aren’t ready to adopt machine learning technologies since their data sets aren’t clean. Organizing the data is essential to getting the most out of the technology investment and embedding transformation into a company’s DNA.
To get started, companies should start asking themselves what decisions need to be made to prioritize the data. Next, everyone needs to get on the same page to define the end goals of putting new technology in place. This is where the top-down approach to transformation comes in: what are the customer and employee experiences you’re trying to achieve? How are tools like AI, blockchain, and RPA going to help you reach your business goal? It’s critical to consider your risk, return and investment in these planning phases before moving into tactical approaches.