Big Data – What A Rush

Data, data, everywhere, the big data rush has some similarities to other near and far, fresh and old events. The dot com rush of the late 90’s, the social media rush a few years ago, and now this. Obviously we have seen other rushes such as the gold rush, the real estate boom and back in Europe, the tulip rush.

The key themes are that these were new concepts for a broader audience and reached a critical mass. As the interest grew, companies often rushed into an area without proper preparation, fearing a competitive disadvantage or looking at it as a major game changer to leap frog competition. Each of those sound ideas, maintaining competitive parity, gaining a competitive advantage, first mover advantages, follower dividends due to investments in awareness by the first mover. Being an agile practitioner, I firmly believe in the launch and iterate approach, but that launch has to be in the right direction.

Among the largest risks faced by organizations was insufficient access to expertise and talent. With the gold rush of sorts, the demand exceeded the supply of immediately deployable resources. Companies either had to make do with what they had and try to build skills and knowledge base, work with consulting companies, or bring in independent contractors. There were lopsided teams with either too much or to little of technical, creative, strategy or operational representation. This resulted in lopsided strategies or lopsided execution.

We continue to see the impact of that even today. The silo that digital strategies operate in, the failure of companies to employ segmentation, profiling and targeting in new channels, even though they may be common practices in their direct or brick strategies and campaigns. As the industry moves around to understand the gaps in customer experience due to nonalignment between the brick, click and flick approaches. Businesses are just beginning to understand that to go digital is not just to have a website, mobile site and social presence, but the fundamental redesign of their business in order to be a more open, responsive, and connected business. The same will be the challenge for big data.

So what does it mean for big data? This is no hype. Big Data is real and it is here with an impact and potential we are all still looking to understand. There are many opportunities for businesses to utilize the data, whether sourced internally or acquired from data sources, and really leapfrog, or even teleport into a new business dimension.

Take a step back and get organized. Get the right players involved, empower them and source the relevant data. A misstep can not only be expensive, it can be dangerous that it can set you back or give you wrong beacons.

1. The acquisition or collection cost of data is high, requires capital and is a major undertaking with a high commitment. Too much, too little or not the right type of data can all create havoc.
2. Supporting infrastructure: hardware, software and humanware; cleansing, housing, data quality, data security, data governance, data scientists, analysts, analytics, analytical tools, reporting tools and apps, visualization tools to name just some investments.
3. Strategy and Operations: businesses must start with defining the lever they are trying to pull, or create, and whether the new insights will help them make faster, better, newer decisions. Good data scientists and analysts are phenomenal resources, but they have to work in a team where someone is looking at the business, opportunity, industry, competition from a strategic point of view, and ability to execute on data with higher velocity and variety in order to drive the real value.
4. Holistic versus standalone: the larger the company, typically slower it is to move, and thus it leads into situations like the standalone digital divisions noted previously, which were just a duct-tape or bandage. With data, its important to have an enterprise wide approach to handle structured data as well as unstructured data together. This can give the exponential gain. Metrics based on old data can be quickly supercharged with more insights to be more accurate, or faster, and in parallel work should be done to determine what else can be done.

Needs and key questions must be identified by the right team given the charter to make this an enterprise wide initiative, a transformational work of sorts. Based on this, a data plan should be developed to acquire/capture the data at the right time. If the data can not be utilized, then the intellectual gratification of analytical and strategic gymnastics aside, it will not help in moving the needle and will only impact the ROI negatively. The right infrastructure should be built for short and mid-term needs balanced with an understanding of the longer term needs for storage, transmission, and analytics.

But leaving it to data experts or analysts may create the same challenges businesses saw themselves in the early days of dot com with developers and creative teams trying to do the work of marketing, legal, and customer service, resulting in some spectacular implosions. They have to be supported and augmented with business partners with the bandwidth and skills to bring the business needs and critical questions to them. If not, the grand experiment may turn up a 42.

The example I often give is that of Douglas Adams’ masterpiece ‘The Hitchhikers Guide To The Galaxy,’ where the super computer earth run by mice scientists for millions of years was to provide an answer to the question about life, universe, everything. The answer was 42. The problem now was trying to figure out what was the question this was the answer to. Please do not get your own 42. Otherwise you may just have to use another Douglas Adams quote to deal with the outcome: “we apologize for the inconvenience” or worse yet “so long and thanks for the fish.”

Author Bio:

Kamal Tahir focuses on innovation, digital strategy, and subsequent product/solution development, launch and growth. Known among his peers as the “Marketechnologist”  Kamal focuses on strategic gains using information, technology and analytics as drivers. Kamal has been a speaker at industry events and has published on the topics of data, analytics, digital strategy and loyalty in various industry publications.

Twitter: @kamaltahir