4 Big Data Truths
We offer four distinct pillars of a successful big data strategy for decision makers in new product development.
By Kobi Gershoni, Co-Founder and Chief Research Officer, Signals Group
Like a dog chasing a car, the last decade has seen organizations chasing after "big data" and its promise to alter the future of business. Fast forward to today, where most have finally "caught" it in one way or another -- but now they're not quite sure what to do with it. That's because "big data" can mean many different things, and it's become apparent that we need to expand what we think of when we talk about data intelligence.
One area that stands to benefit immensely from a savvy data intelligence strategy is new product development, a practice where 96 percent of all innovations still fail to return their cost of capital, according to Deloitte. The stakes for success, failure, and rapid innovation are higher than ever, and powerful intelligence solutions that can take the guesswork out of decision-making can be leveraged to great advantage -- or disadvantage, for those still playing catch-up.
The problem for many enterprises is that most big data strategies have focused on improving business-process efficiency and identifying areas in their existing processes where they can extract greater revenue. They've spent years investing heavily in analytics systems that have yet to show results. They're looking at their own proprietary internal data while ignoring external sources. They're relying on systems built to improve internal processes and systems yet fail to explore where big data might aid with strategic decisions. They leave the insights to IT or the CIO instead of disseminating to teams on the ground actually making decisions. In short, they don't know what they don't know -- including what they should be doing now to gain a competitive advantage from big data and not miss out. Product development professionals are left out in the cold.
If any of this sounds familiar to you, you're not alone, but you are certainly at a disadvantage. To help, I'll explain four distinct pillars of a successful big data strategy for decision makers in new product development.
Pillar #1: Disruption Proof -- The Wide World beyond Your Internal Data
In the information age, to be reactive to market trends is to be late. Within the various types of data platforms or source types -- such as business news, scientific and academic journals, social media, and e-commerce -- decision makers can discover the hidden insights about coming technologies, new products, and unmet consumer needs. Yet many companies are still buried in their internal data and systems that have yet to return on their investment, while failing to capture the wealth of open source information right under their noses that can help them today and would have certainly helped them yesterday.
Mining the right sources available via open source data fundamentally enables companies to gain a competitive advantage. These platforms give decision makers the reason to create next-generation products relevant to future market demands and allow companies enough time to respond efficiently to their competitor's actions. It's open source data that gives decision makers the insights needed to seize opportunities, avoid unnecessary risk, and be proactive rather than reactive to market trends.
Pillar #2: Evidence, not Intuition -- Data-backed Decision Making
This is not your IT team's big data strategy. In order for intelligence to be useful to product development teams, it must be actionable. Insights embedded within big data can give product-development teams insights much faster than other sources while taking the guess work out of processes or decisions that have primarily been based on intuition. However, this only works if those decision makers have access to the intelligence at the point where they actually make decisions.
This means data can't be kept in silos or only in the hands of IT or the CIO. It also means the data strategy must be built from the top down, starting with key questions that need to be answered and decisions that need to be made, rather than the other way around (bottom up). When the new product development research and data approach is decision-driven and connects the dots between what consumers want and what technology can solve for, those assessing big data can create an efficient product development plan to beat their competitors to the market.
Pillar #3: Quick, not Rash -- Agility In the Face of New Intelligence
Intelligence is only as useful as your ability and willingness to use it. With the right big data strategy comes freedom -- and responsibility -- to change direction mid-course in the face of new intelligence. Vigilant attention to signals and access to potential disruptors in real time is a huge advantage for teams to avoid risk and size opportunity. Imagine: the ability to know of a competitor's plans to launch an exact product while yours is still in development and the advantage of adjusting your strategy long before two identical products are launched.
The right real-time open source data strategy can often provide intelligence about competitor movements well before this point, and savvy decision makers will be prepared to read these signals and adjust course as necessary. This advantage is only possible if product development teams are empowered and willing to change direction quickly, a practice that challenges traditional conceptions of research, strategy, and competitive intelligence.
Pillar #4: Always On -- Data Never Sleeps
When the work day ends, data does not. The competitive landscape operates 24/7, and product developers must be able and willing to have visibility into those changes and respond to them at every stage of the process. Data intelligence and monitoring must be integrated into the every-day product development process, not just key moments. Consumer needs and competitive activity are constantly evolving, and ongoing monitoring of relevant business ecosystems and data sources is crucial to survive, let alone break ahead. From now on, if you want the victory of being first to market and solving unmet needs ahead of your competitors, you must stay vigilant about your big data strategy and habitually wrap intelligence into every key business decision.
A Final Word
True to its promise, big data has changed the game for business practices across industries and disciplines. The biggest advantages, however, are there for those willing and able to grab them first. Right now, the analytics race is on for new product development, and those companies and decision makers who haven't yet faced these four big data truths are most assuredly going to find themselves lapped. The time is now to set the groundwork for the big data practices that will give you a competitive advantage before other companies have the chance to catch up -- and long before you find yourself left in the dust.
Kobi Gershoni is co-founder and chief research officer of Signals Group, an Israeli-based tech company that has developed an analytics platform for new product development innovation. Kobi has extensive experience in conducting research for multi-national corporations and venture capital funds. In addition, Kobi served in an IDF intelligence unit as a senior analyst and information officer. For more information on Kobi, Signals, or insights into big data, visit www.SignalsGroup.com. You can contact the author at firstname.lastname@example.org.