The biggest challenges companies face when implementing Big Data are budget constraints (Capgemini)
“50% of US executives and 39% of European executives said budget constraints were the primary hurdle in turning Big Data into a profitable business asset. Rounding out the top 5 challenges were data security concerns, integration challenges, lack of technical expertise, and proliferation of data silos.” (Capgemini)
Data analytics is continuously evolving as AI and machine learning applications get faster and smarter. The benefits that may be gained by analyzing massive data sets identifying in seconds patterns, signals, and relationships between nonaligned and aligned areas is intoxicating for savvy companies seeking to innovate. We recognize that companies can make faster and better decisions with strong analytic teams interpreting the findings. Look at what information-driven analytics has done already in cool improvements around us. There are so many good examples of this. Take transportation systems, the use of information analytics to course vehicles round congested areas in actual time is one simple example. Another, that literally may have saved the restaurant industry during the pandemic, is meals delivery services which depend on data collected to forecast demand on menu items, key order times, navigation around cities and streets not to mentioned detailed knowledge individual’s meal preferences. Data helped to optimize driving routes for more efficient delivers.
As data analytics becomes more sophisticated, we might anticipate revolutionary disruptions. However, economists report spending greater funds per capita on research, yet there is a significant decline in rate of successful innovation output. One motive for this could be that we are mistakenly focusing an excessive amount of on R&D instead of on innovation output which takes exceptional justification, funding, and resources. What does data analytics have to do with innovation? Everything! Research is crucial but just one part of a puzzle for developing new products and services. Today, innovation requires a sophistication in data analytics interpretation. There’s also a need for the curiosity, for human evaluation and a bit of intuition and intelligence. Companies need an astute cleverness like no other time in history and an ingenious approach to taking research and turning it into something new and worthwhile. The process must be diligent, but it must also be agile. Too frequently, organizations get bogged down within the details of research and improvement, without truly questioning outside the boundaries of a container process. As a result, we have delays in the process often stalling out for lack of resource allocations. Even worse, companies not focusing on deep understanding of their data may misinterpret the analytics leaving more to chance that to solid pathways.
It’s worth saying, placing a greater emphasis on creativity and innovation is imperative vs. traditional research and improvement methods. As is deeply dissecting the data in your business. Where does all that data live? What are the hidden signals of the data, what types of converging uses (products/solutions) could you turn that data into?
We are in an era of new growth. Poll your customers! They are changing rapidly and challenged with keeping up with the speed of change but know they must. Where are they doubling down their efforts? How well do they understand their own data? What products and services are they developing, who are they collaborating with and a better question, why are you collaborating with them to innovate around their future needs? Are they investing in developing a more tech and analytic savvy organization? Better question, is your company?
As cliché as it is data is the new oil. Data will be producing its own data (it’s happening today) known as synthetic data. According to Gartner, “By 2025, synthetic data will reduce personal customer data collection, avoiding 70% of privacy violation sanctions.” This begs to question the emphasis companies are placing on developing the skills sets of the organization around analytics and data. And simply put, as oil has an expansive array of products and uses, we’re now in an era of inventing new energy sources to reduce even eliminate dependencies on oil. How might data fit into the effort to transform these dependencies? Data is essential for electric and autonomous vehicle development. Innovative companies are undertaking long tail efforts to drive the next generation of IoE (Internet of everything). Data is the fuel. Let’s explore four ways that organizations can use records analytics to power innovation and stay ahead of the competition.
- Design new products that think for themselves: understanding data from a variety of sources may trigger new types of needs and possible new products that could be developed. For example: understanding water needs for new smart and innovative cities being designed takes enormous planning. A partner to Plazabridge Group, designs digital twin environments for the water sector. Cites like Singapore, Houston, Dubai, must anticipate the growing needs for water and plan design and building based on anticipated needs but also, they must plan for worst- and best-case scenarios. They must plan for leakage, or contamination or other possible scenarios that may impact water supplies. Digital twinning these environments is the most cost-effective way to simulate new innovative methods. Leveraging as much data as possible as well as generating newly created synthetic data cities can plan more economically, they can execute faster and prepare for events that may occur. Understanding these models around water, suppliers may produce products that help cities build these digital environments. Not just for water systems but for any part of businesses today; manufacturing, facilities management, construction…
- Not all innovation has to be moonshot inventions. Simply identify unmet wishes of customers, consumers or the market creating engaging products and services. UBER goes from just carting us around leveraging an incredible inventive back in logistics infrastructure to launch UBER eats! Why not, the drivers are already out and about, the data collected indicates the most popular spots riders go to for coffee, lunch, dinner, drinks… UBER analysts have vast information on customer interests in turn turned from few riders during a pandemic to delivering food as an essential business during the pandemic. A pivot turns into a scalable source of augmented revenue as the shelter lifts and people get back to riding.
- So much opportunity exists to improve customer engagement: records analytics can assist businesses to better understand their clients and their wishes. This expertise can then be used to improve customer service and support future-proofing your business.
- Extend efficiency: data crunching algorithms, digital twinning, AR/VR simulations and access to remote experts will help corporations to streamline their operations, digitally transforming themselves for greater efficiency. This increased efficiency can lead to price savings, which can be reinvested in innovation.“90% of CEOs believe the digital economy will impact their industry, but less than 15% are executing on a digital strategy.”
— MIT Sloan and Capgemini. Seek out experts and industry mentors to help your organization make these shifts. We often fear what we cannot see, the beautiful thing about digital world is you can build a virtual environment visualizing the unseen and plan for all types of scenarios. A model we developed (not dependent on virtual or digital anything in fact) at Plazabridge Group is around the CIA’s The Phoenix Checklist. Strategies for Regenerating is our formula for going deep into understanding problems, future opportunities, needs, anticipating deeply the “What ifs” of every possible scenario. When done leveraging data and analytics the possibilities become endless.
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