A requirement to have a strategy on how your organization manages data is more prevalent than ever. The explosion of big data in recent years means this is no longer a buzzword - businesses need to take action to harness its potential now if they want to stay relevant and future-proof their business against the competition.
Simply put, “big data” refers to large volumes of data sets, often available from a number of different sources that can be analysed to provide faster, more insightful information on entities of interest, including customers, suppliers and employees.
With new data created every second, our ability to create, analyse and investigate data grows every day. However, currently, less than 0.5% of all data is ever analysed and used because embarking on a big data project isn’t easy. According to IDG Enterprise 2016 Data & Analytics Research, 90% of those surveyed ran into challenges with their big data projects.
Challenges such as storage and analysis of growing volumes of data, delivering insights in a timely fashion, and integrating, validating and securing big data, can often be a deterrent to starting a big data initiative. However, with a solid strategy and a structured plan on how big data will be managed, organizations should see value quickly and benefit from the investment in the long run.
Designing a coherent, clear and concise strategy needs to start with identifying and defining the business challenges that exist across the organization. Whether your issues relate to increasing customer retention, improving the reporting of network assets or reducing your cyber threat levels, by pinpointing where your issues lie will bring focus to your solution, set clear goals on the value you’ll deliver and help companies clearly measure return on investment.
From a commercial real estate perspective, how can a property developer create a long-lasting sustainable environment that will add value to its tenants and visitors whilst maintaining an efficient operating cost? How can big data be used to inform design and construction of spaces, or maximize the potential of a building’s assets, which will often outlast its creators, and be better future-proofed?
Consider how tracking factors such as air temperature, radiant heat, air movement, humidity, light, sound, carbon dioxide and monoxide, along with various other pollutants emitted from building materials can improve building and energy efficiencies. The huge volume of data can be analysed for patterns, and used to manage temperature variations throughout the building and introduce interventions such as filling a space with plants to address carbon dioxide levels.
By supporting businesses to better connect and correlate disparate sources of data, companies can unearth a treasure trove of insights that will help drive efficiencies and reduce costs, analyse risks, optimize current offerings or develop new ones, and guide smarter strategies now and in the future.
The Malaysian government’s move to implement a big data plan to help companies use data and analytics more effectively, will not only create economic benefits but ensure organizations operating in the country are equipped to stay competitive on a global stage. Malaysian banks are leveraging their data to reduce costs and risks attached to their collection of monies. By profiling and scoring customers by their propensity to pay, they can optimize front line staff to focus their efforts on the activities that will deliver the most effective collection outcomes.
Local airlines are also using data to affect decision-making in a competitive market. Using historical booking trends and real-time signals, airlines are able to identify under-performing routes and intervene to better optimize yield and revenue.
As technological efficiency grows, big data will be less about the size of a dataset and more about high-level analytics and methodologies used to gather insights that inform data-driven decision-making. Capturing the power of big data needs to be accompanied by a fundamental cultural shift in the way businesses operate.
When designing a data strategy, organizations cannot ignore the role people will play in implementing data-driven initiatives. How will your staff use the information it captures and engage with the insights it produces to deliver value? And how will technology enable individuals to act faster during the value-creation process?
Consider a city where data is being collected on electricity meters, traffic lights, trains and the like. This information can help organizations understand performance and usage of these assets and use that information to predict equipment failure. This can then be used by staff to influence maintenance schedules, estimate future demand and apply interventions to avoid breakdown or oversupply.
Solving the big data problem is about understanding the value chain of big data and re-thinking its purpose and how it can be embedded in assessing the return to shareholders, customers and communities across each stage of the strategy.