Digital Transformation – Too Difficult?
Digital transformation is now back in ‘must do’ land – in again, out again. I can only surmise that a few years back none of us were ready. I’m not sure we are now.
A fundamental component of digital transformation is ‘disruption’ – not a word that usually carries warm and fuzzy connotations. For those risk-averse industries or companies that have environments that still rely on siloed applications, a management attitude where getting the job done is more important than innovation, or where a groundswell of end user action is not particularly unusual, how do they get dragged along to embrace digital transformation? I guess, screaming and kicking, if they go at all.
What approach can facilitate this transformation and that promises 12 percent higher revenues, amongst other benefits? Technology would be a good start. And if you are in a risk-averse or low margin-industry, technology can still be your best friend. I have written about many a study where executives and staff have no idea what data they have. It’s like anything else in life – knowing where you’ve been helps you know where you’re going.
We all have data, and plenty of it. What we don’t all have is the ability to analyze that data to drive business initiatives. Evaluate and grab a technology that supports digital transformation – not a technology that is limited to improving a specific function in the here and now. We are looking long-term here.
OK, back to embracing digital transformation through technology. IBM tells us that 90 percent of the world’s data was created in the previous two years. To be more effective as an organization, it would be beneficial to know what’s in your data. It would also help to identify old, stale data of no value, to take that out of the analysis. What we all want is a technology tool that can be used as a long-term solution that will facilitate our goal of digital transformation, as well as deliver value now.
Years ago, one of our clients did exactly that and was able to save literally millions of dollars. It ‘thought outside the box.’ Why? Because it needed visibility into its data – unstructured, which was the largest portion, semi-structured, and structured. To this day, many vendors try to force fit unstructured and semi-structured data into a structured format. I don’t understand it. It doesn’t work. To me, it doesn’t even make sense. You lose the transcendental qualities, the meaning or essence of unstructured data, and the ability to extract all the hidden facets that give content meaning. Our client needed a solution that encompassed all forms of data and retained the meaning in the content.
Instead of going through a laundry list of our core auto-classification technology features here, you can read the case study about how this client used our technologies to impact the bottom line, in a big way. This is a great example of aligning your objectives, however big or small, to achieve digital transformation.
Our technology is platform-agnostic, it is a framework extendable to any application that requires metadata, it supports workflow processes that are easy to deploy on specific content – and I do mean easy, it can be used by business staff, it runs in real time, and it is highly scalable. So I did end up going through a portion of the features laundry list. If you need auto-classification for data analysis, text mining and analytics, you would use our solution.
The point is that on this rocky journey, you should choose technologies that are viable both now and in the future. Don’t select options that offer a stop-gap, or have promised future features, or are limited to solving only one problem or process. Select solid, proven technologies that have staying power. If you do this, maybe digital transformation is in your future.