Next time you find yourself wading through data points, sifting out patterns from the noise, hoping to catch the rare pearl of insight to affix to your business plan, know that you are not alone. Employees worldwide incessantly engage with data, and the companies they work for urgently execute on data-driven strategies in a race for better, faster results. Data pervades the workplace and continues to grow in terms of volume and variety: Research suggests that by 2020, the number of connected devices will more than triple, tens of thousands of data scientist jobs will be in high demand, and the majority of sales decisions will be data-driven.
But using data regularly doesn’t mean that employees truly understand it – or are comfortable with data practices. Specific obstacles prevent individuals – at the top and bottom of the organization – from eliciting effective insight. Forrester’s Business Technographics® and ConsumerVoices MROC data shows that while individuals rely heavily on data for decision-making, they still grapple with key challenges regarding the accuracy, volume, value, and security of the data they use:
Recently, I talked with the CEO and founder of reBuy about the shifting dynamics in the retail sector as a result of digitalization. The use of data has evolved to the point where data has become the enterprise’s most critical business asset in the age of the customer. The business model of reBuy reCommerce — the leading German marketplace for secondhand goods — can help CIOs understand how the intelligent use of data can significantly disrupt a market such as retail.
The case of reBuy offers interesting insights into how the wider trends of the sharing and collaborative economy affect retail. If you can buy a good-quality used product with a guarantee for half the price, many people will not buy the product new. Many consumers increasingly accept product reuse and see it as an opportunity to obtain cheaper products and reduce their environmental footprint by avoiding the production of items that wouldn’t be used efficiently. The reBuy case study highlights that:
Business technology is taking the sharing economy into new realms. The reBuy business model demonstrates that consumers are starting to push the ideas of the sharing economy deep into the retail space. CIOs in all industries must prepare for the implications that this will have for their businesses.
Standalone products are at particular risk of sharing dynamics. The example of reBuy shows that businesses that sell plain products will come under even more pressure from shifting shopping behavior, where people are increasingly satisfied with buying used goods. These businesses need to add value to those products that are not available for secondhand purchase.
Open data is critical for delivering contextual value to customers in digital ecosystems. For instance, The Weather Channel and OpenWeatherMap collect weather-related data points from millions of data sources, including the wingtips of aircraft. They could share these data points with car insurance companies. This would allow the insurers to expand their customer journey activities, such as alerting their customers in real time to warn them of an approaching hailstorm so that the car owners have a chance to move their cars to safety. Success requires making logical connections between isolated data fields to generate meaningful business intelligence.
But also trust is critical to deliver value in digital ecosystems. One of the key questions for big data is who owns the data. Is it the division that collects the data, the business as a whole, or the customer whose data is collected? Forrester believes that for data analytics to unfold its true potential and gain end user acceptance, the users themselves must remain the ultimate owner of their own data.
The development of control mechanisms that allow end users to control their data is a major task for CIOs. One possible approach could be dashboard portals that allow end users to specify which businesses can use which data sets and for what purpose. Private.me is trying to develop such a mechanism. It provides servers to which individual's information is distributed to be run by non-profit organizations. Data anonymization is another approach that many businesses are working on, despite the fact that there are limits to data anonymization as a means to ensure true privacy.
Once again, the mobile world is getting ready for the most important mobile event of the year, the Mobile World Congress (MWC), which will take place in Barcelona from March 2 to 5. In my role as analyst with a focus on CIO requirements, I expect the following themes to dominate this year's show:
Everybody will talk about data — and many about data privacy. The long-anticipated marriage between big data and mobility is finally happening. I expect just about every vendor at MWC will claim a stake in these mobile data wedding arrangements. However, many big data business models remain building sites, and it remains far from clear which players will benefit via which types of business models. The growing awareness of regulatory constraints on the use of customer data as well as what the Financial Times recently called the "creepiness quotient", i.e., hyper-personalized advertising, further complicate a convincing business model for mobile analytics on a mass scale. Despite all the hype, mobile data is one of the must-focus areas for CIOs who attend MWC.
If you think Big Data is something only B2C marketers need worry about, you’d be wrong.
As business buyers turn to the digital world to help them explore and solve pressing business problems, marketers will find that the data needed to propel their firms into the digital future is increasingly big.
The challenges we face in closing the gap between the amount of data available and our ability to get value from it are equally big. Nevertheless, to become customer obsessed requires understanding your buyers much better and data is the key to that understanding. During Forrester’s Forum for Marketing Leaders last week, I told B2B marketers that it’s time to make a date with their big data destiny. (The prior link is to our forum coming up in London -- you can also listen to my April 30 webinar to learn more on this topic.)
My colleague Brian Hopkins believes that - to exploit the business opportunity hiding in big piles of data - marketers must understand that data is increasingly: