Lenovo

Much has been written and said about the new found power of DATA. In fact it is hard to get away from the data talk and the related jargon if you are part of IT, marketing or technology these days. It goes without debate that the fast paced digital world is in the midst of a dramatic and profound transformation. This is hardly surprising given that there will be roughly 10B mobile devices by 2020, a billion searches are performed on Google each day, a staggering 294M emails exchanged daily and even a mind numbing 50B messages are exchanged on Whatsapp daily. It is safe to assume the changes are irreversible and will inevitably lead to possibilities that will impact society profoundly.

There is a certain level of excitement about the possibilities, from new drug development looking for cures for rare diseases to underwater oil exploration to mapping the entire human genome. At the same time there are serious concerns about moral and ethical dilemmas arising from privacy, security and in some cases the implications of artificial intelligence driven by data. The ability to follow, snoop, customize, segment, target the digital persona has gone up significantly, in fact, to a point where it is a serious concern for individuals and governments. Today’s immediate challenge of course is that companies have significant challenges before they are going to be able to take advantage of this paradigm shift. That is the crux of this discussion. Several companies have ambitious plans (23percent of companies polled) on rolling out big data initiatives to drive internal productivity and external sales and marketing activities. However, the success of these initiatives have been all over the place, some companies that deal with data and have done so for years have made some progress, but still not at the hyped up level it is made out to by those that sell these solutions. While new data is available in shiny formats and new jargon, old data suffers from legacy and traditional problems of integrity and compatibility. The costs for cleaning and transforming this can be enormous and managing and maintaining the ecosystem time consuming and cumbersome, not to mention talent requirements that is sometimes difficult to find. Bottom line, if you are an organization that wants to transform yourself into a thoroughly data driven organization there are more things beyond technology that has to change very fundamentally. These are more core and difficult change management challenges than most people can overlook. Here are some observations, problems we have seen, some common mistakes people make, solutions and recommendations if you are embarking on a data journey to transform your business.

“Take it seriously, involve everyone; the skeptics and the evangelists, make it visible, and use experts to make it a company core competency”

Data Is Never Clean

Operate under the assumption that data is never really clean. It requires people and processes and tons of energy to visualize and get into formats that are ultimately useful. The process is continuous and will continue to be challenged by evolving technology, business requirements and the very dynamic customer landscapes the business intending to deal with it finds itself in. If we have to make sense of stuff we need to be able to handle multiple types of data in a flexible way and make it clean and work nicely with everything in your system. We need to be realistic about this and build systems that allow for backward and forward integration of technology so we don’t end up with monolithic solution that later become boat anchors.

Message: Be ready to go through a painful process of inventorying, ETLing and integrating data and sources as you begin to think about making sense of the various disparate systems.

Technology Is Important, but Really Not a Deal Breaker

Move under the very real assumption that technology will evolve rapidly. We will see lots of innovation on data management solutions driven by VC and social funding. While you don’t want to move from one shiny object to another, you also should not lock yourself into technology that is old and clunky if you have access to new stuff that makes your life easier. So develop and use frameworks that are built with flexibility in mind, preferably with the explicit mandate of using a building blocks approach.

Message: Think through clearly the various levels and layers of data and technology. Design for flexibility, don’t put all eggs in the same basket ensure individual pieces aren’t TOO big to fail

Use Culture as a Pivot for Change

Organization culture in many ways drives your data strategy success and its adoption even more than your choice of technology. Here is the challenge— moving from data reporting and some insights to driving significant and deep rooted insights in a continuous manner. Many individuals and leaders are skeptical because their experiences have been painful, inconsistent and prone to wide fluctuations in quality of insights. So trying to do an organization wide transformation requires fundamental cultural transformation. This is time consuming, challenging and expensive.

Message: Take it seriously, involve everyone; the skeptics and the evangelists, make it visible, and use experts to make it a company core competency

Perfection Is Overrated, Expect to Fail Multiple Times

The whole data transformation exercise can be incredibly frustrating to both the ones developing the systems and the ones using them. The funny thing however is that these systems should be precisely about that aspect, it should be designed and built for people to experiment and try different things. The more there is room to experiment, the better the adoption and ultimately the quality of output. So it is not uncommon to have several projects in flight and several experiencing multiple failures, from small ones to really big ones. Small one can be a data compatibility issue between two systems that pushes timelines, a more serious one is investing significant time into an initiative only to realize that you cannot get to where you want to go and have to reset and restart. As a leader you have to change your mind set on what constitutes success.

Message: Empower your people to be able to play around with stuff, traditional measures of success may be limiting, new measures such as ‘time to value’ or other metrics may be better suited

In conclusion, technology may not be the biggest obstacle for organizations as they try to transform themselves into level 5 data organizations, the company’s culture might be. It is important to understand, articulate and execute on a deliberate strategy that looks to fundamentally change the company’s thinking and culture about data.