Enterprise digital fitness starts with the purpose, shaped by the strategy and built through practices.
Digital is the age of change, there are an abundance of information and emergent digital technologies such as SMAC (Social, Mobile, Business Analytics, and Cloud) around, but it doesn’t mean organizations will become a high mature digital business automatically; many organizations have got the symptom of “data obesity,” "information misleading" or “technology addiction.” What’re the root causes and how to achieve the enterprise’s digital fitness?
Digital is the age of change, there are an abundance of information and emergent digital technologies such as SMAC (Social, Mobile, Business Analytics, and Cloud) around, but it doesn’t mean organizations will become a high mature digital business automatically; many organizations have got the symptom of “data obesity,” "information misleading" or “technology addiction.” What’re the root causes and how to achieve the enterprise’s digital fitness?
Digital fitness is based on strategy competency and execution effectiveness: The emergent technology trends are where the opportunity located for real competitive advantage from investments in IT into the future. Whether an organization realizes the potential advantages of these technologies depends on many factors. However, there are a lot of companies jumping on the analytics bandwagon because it is the "next big thing," without any understanding of how it fits into their strategy. They seem to think that building a data warehouse and collecting lots of data will somehow provide value. What is required is having a strategy that integrates these technologies across the entire enterprise, including how best to source them. While there are always risks for these types of initiatives, the biggest risk (often overlooked) is to not have a good strategy to deploy them.
Either information or technology is meant to the end, not the end: Many companies don't seem to have learned the lessons of each wave of new systems over the years that a system can only provide value if you have a clear understanding of how you will use it. It is like any tool. It doesn't matter how good the tool is if you don't know how to use it properly you won't get good results. This is, even more, important for systems like Big Data, where having the data and analytical tools don’t provide any insight or help take the right actions associated with their outputs. It takes the proper balance of knowledgeable IT people building the appropriate infrastructure, working with business people to develop a clear strategy, and then executing effectively as a team.
Mind IT-business integration and IT-customer alignment gaps: IT-Business-Customer alignment, the converged business-IT governance, the integrated digital platform, and IT as the business are all critical issues to mind the digital chasms. Although the global gap has slowly improved over time, the total/comprehensive average maturity remains just over 3.0 (out of 5). The important point for such digital brainstorming is that given the lessons that we have learned regarding alignment, in concert with the integration of these SMAC+ technologies and the increase in enterprises looking to leverage IT for revenue-generating initiatives, we have a significant opportunity to make meaningful strides in closing the IT-customer alignment gap, beyond business-IT alignment. There are ways to find the signals amidst all the noise. It starts with a plan. From there, IT and the Business need to integrate and act as one in a flowing process that's ever agile, because, with the accelerating digital speed, everything is always moving forward promptly.
Make the right choice: There seem to be three choices organizations make: ignore new technology, jump on the bandwagon even if you don't know what you are doing, and embrace the new technology finding ways to create strategic value. The third option is the right one. But the first two are far more common. The point is that one has to know what they are using the data for and what they are trying to analyze plain and simple. A lot of companies end up with Data Obesity because they don't know why they are keeping all of this and what they are trying to analyze. "Data hoarding" is a real problem. The impact on companies that don't get this is more data obesity, more cost, and more risks unless the business can get back to basics and really define their requirements of what they need to keep, what they are trying to achieve with Analytics, and understand what they need. The business usually drives the data hoarding problem as they don't understand the cost of it, nor do they care... They just assume they might need it and, therefore, continue to keep it around. It's not worth the cost, and it's bloat.
Hence, to achieve digital fitness, start with a digital fitting mindset to set the principles, the strategic competency to diagnose the problems, the execution capability to take actions and it takes practice, practice, and practice.
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