Being resistant to IT is often due to lack of knowledge and/or to security and privacy concerns. Talk about technology adoption and you will likely generate a debate around data ownership, location, security, etc.
However, the question today is no longer about the value added by each one of IT trends, but how to combine them to create more value. Technology is shaping businesses and operating models like it never did before.
Take the insurance industry as an example:
“A full transformation to becoming a digital company could cut an insurer’s combined ratio by 21 percentage points, in other words making the firm more profitable. Expenses could fall by 10 percent of premiums and claims by 8 percent. The insurance industry is in danger of falling behind other companies because it is not interested in the latest digital technology”. (Insurance industry drags feet on big data)
Security and privacy
Companies are particularly concerned about data security (a valid one I must add), which should not, however, be taken to the extreme. Too much protection makes it nearly impossible to access data outside of the premisses, and consequently, it limits the potential business benefit that can be derived.
The key question is not how secure the data is, but how much it will help people and organisations. It’s all about agility, usability and speed of accessing the information and USING that information.
Take for example the flexibility of scaling up or down businesses via mergers and acquisitions (M&A). Integrating IT assets is much simpler, faster and cheaper if solutions are protected but accessible.
Available data for companies to work with also enables better decisions. Strategic Analytics is not only about data mining but, more importantly, about data interpretation. Careful though:
“Not everything that can be counted counts and not everything that counts can be counted.” (Albert Einstein)
Numbers and analysis used for strategic decision-making depend very much on the models and algorithms created by organisations. Decision makers should not blindly trust the data given by analytics as this is information spit out by an algorithm; instead they must look at that information and put it into context. This human intervention combined with long-term data driven models, gives managers a better view about patterns and trends, and hence are often better predictors. After all, if the end-question is budget definition, it is not enough to look at the previous month’s data but rather to a longer period of data, right?
There is a great potential here. Creativity is now key to foresee challenges even before they happen, and not just to use the data available to resolve existing business questions as it was once.
Organisations need to be mindful of their needs when assessing IT readiness. Successful adoption of technology is part of a mission that implies having clearly defined goals and strategy and lower the barriers of resistance.
Being aware and being resistant are two different concepts. Which one prevails in your organisation?