The data revolution is gaining pace at breakneck speed, and we are finally towards the latter end of its implementation. Many inroads have been made by important stakeholders, and numerous organizations are currently trying to incorporate a data culture within their workplace. Future predictions suggest that every company will eventually be part of the data brigade and will benefit from the use of data analysis tools.
How to become a data/information company
With growing hype across the market, many organizations want to know as much as they can about the intricacies involved in becoming a data/information company and what they need to do to become one. Although the questions are many, it is easy to answer them.
Being a part of the big data revolution is no different to what it was back in the day. Similar motivation is needed, and organizations need to know the importance of the process and the benefits that it would bring to them.
The biggest benefit motivating organizations into taking the leap forward is the promise of enhanced customer experiences. Customer expectations are growing, but organizations currently seem lost for action in regards to what to do in the face of such challenges. They do have the willpower for change, but that willpower requires extensive investment and the promise of better operations to succeed. The use of data related to customer information has really helped organizations customize offerings and give their customers the experience they need. Business models that didn’t use data previously have now latched on to the revolution in data and have started crafting their offerings in such a way that they sound personalized to each and every customer.
The data process starts through the extraction of raw data, but this is not where it stops. Most organizations believe that they have done their job by extracting data, but, believe me, this is only one quarter of the job done. The main focus of the data revolution is on the value that is taken out of the extracted data. The data wouldn’t amount to much if the organization wasn’t able to find any value in it. Only if there was value being extracted through the data would this process be considered successful.
With information from the data in front of them, organizations are eventually expected to act upon them. These actionable insights propel organizations into action and force them into altering their products and services based on these insights. Again, customer experience sits at the center of the process as the ultimate aim is to satisfy the customer and give them an unparalleled experience.
Maturity phases to becoming an information company
Becoming an information company and eventually achieving maturity in monetizing data is definitely not for the faint-hearted. The process requires a lot of primary and secondary skills and needs lot of human investment other than the capital investment that is being provided.
Any organization that is looking for maturity in data monetization needs the following steps. We are focusing more on the internal facets of being a mature data company than the external aspects.
- Perform Business Intelligence: Look at all systems external and internal and perform a business intelligence trial by creating dashboards to see where most of your data is going. Change things around you based on what you are learning. The use of predictive analytical tools and master data management processes for gathering internal insights can be extremely useful in the long run. The dashboards you create will help you see who’s using your products or services and how you can help serve them better.
- Extend Products and Services with Data and Insights: The insights you get from the data can be used to extend products and services to your clients. Once you know where most of your services are going to, and have a thorough plan on how you can leverage this opportunity, you can actually use the insights to extend products and services to the right people.
- Deliver Information Services: Finally, the most important step to becoming an information company is to deliver information services to clients. There have been numerous success stories of clients jumping on the information bandwagon by providing prescriptive and predictive analysis to their clients. You, too, can build a list of clients who you can provide information services going into the future.
Implementing data monetization strategies
Once you have reached the maturity stage, you will have to go towards the implementation of data monetization strategies. Now, the tips above might come useful here as well, but the following points well help you out in the monetization process:
- Establish a Vision: Corporate executives within a company should extend the vision for monetizing data and should allocate resources including workforce time and investment towards ensuring that the data is properly monetized.
- Agile Multi Disciplinary Teams: Data can be monetized through the use of multi-disciplinary teams made up of agile data-architects, analytics specialists, product managers, marketing professionals and application developers.
- Develop a Competitive Culture: Unless it is properly communicated and made functional across the workplace, data remains worthless. To extract the most out of data, you need to create a data-driven culture.
- Convenient, Secure Access to Data: Data can only be monetized if it is clean, consistent and accessible, along with being voluminous in size.
- Management and Advanced Analytics of Data: The five data management layers of engagement, development, integration, modern core IT and data are the key components of a digital business. Data is only valuable after it has been analyzed and when it is managed carefully.
Use cases of data/information implementation
Real-life examples of organizations joining the digital revolution and altering their offerings in the process serve as an example for all organizations in the future to follow. RELX group is an organization that has set a major precedent for any organization looking to become an information company. RELX, which initially started as a company that provided printed information to clients, moved on to digital information services. RELX realized the potential in the industry and added information to their selling process. Now RELX operates as a successful organization in predictive services for researchers, doctors and lawyers. The company helps run predictive services through the use of their expertise in information and data analysis.
Otis Elevator is another example of an organization that participated in a digital revolution and benefitted from it. Otis faces the challenge of maintaining more than 2 million elevators across organizations and cities. To keep pace and to increase its level of service, Otis underwent a major technological revamp.
Accordingly, Otis started by analysing big data technology trends around the company’s more than 300,000 connected elevators, all of which generate data of their own. The data generated from these elevators, and other newly-connected elevators that leverage IoT for real-time data collection, can calculate when an elevator would go out of order based on its health and what can be done to halt the downtime, or in other words, the need for predictive maintenance. The data that Otis generates can also help buildings control the flow of people across floors and learn what can be done to ensure that flow is maintained and optimized. By stepping into the field of data and information, Otis has not only broadened the horizon of what they were doing but has also initiated a whole new realm for better building management in the smart world.
Finally, it would be unfair to leave out Netflix, the entertainment giant, from this list. Calling Netflix’s data strategy a business transformation would be wrong because this is something they have always embedded their culture on, but Netflix has never shied away from taking risks to adapt to the needs of clients and give a stellar performance. They have made huge strides through their personalized offering and exceptional understanding of enterprise data insights. They achieved all of this through the presence of a dedicated team and exceptional data analysis tools. Such is their dependency on big data analytics now that their data algorithms help save over $1 Billion in the form of customer retention every year.
With success stories to learn from, this is your chance to plan your data transformation and alter your offerings to please your customers and give them the required customer experience. With due efforts, you, too, can achieve success in this regard.