Digital Transformation How-To Guide #11: Analytics and Data in your Digital Transformation

Author by Bill Topel

Author’s note: This ninth post in our series on Digital Transformation continues to lay out what a truly modern approach to IT “looks like”—this time with regard to Analytics and Data.   Data has always been the soul of any business. Regardless of what industry you are in, companies for years have collected, combined and used Data to determine the health of the business. In the new digital world, Data has given us the ability to not only report on the business but also tools to predicted the future, recommend purchases and discover new facts. One of the largest changes about the usage of Data in a digital landscape is that we are not just using our own Data. Instead, we are combining the traditional Data we collect, Data customers enter, industry Data, environmental/governmental Data, and sensor Data into complex and rich information sources. These new Data sources are providing new and unique discoveries while driving massive changes for companies. If you are not leveraging Data this year are you still going to be in business next year?
 
Amazon was one of the first companies to leverage product information, individual customer purchase history, other customer purchase history and seasonal reference to deliver a recommendation engine that changed e-commerce forever. Uber combined customer vehicle preference and location Data, driver location Data and optimal route information to build an industry-leading transportation platform. Netflix built its business on the strength of predictive analytics that gauged something as personal as taste in movies.
 
Today, Data is the most important asset a company can collect, maintain and leverage. Whether you are collecting information from your own business applications, information from your customers’ wearable devices or historical weather patterns, Data curation is a top priority for a Digital company. The successful companies of the future recognize that Data can be used to optimize existing operations, discover new customer insights, recommend production or inventory levels, and even diagnose health issues and recommend treatments.
 
Digital Transformation is driving change in the way Data is leveraged throughout the business—and the business is driving change in the way IT is leveraged to change outcomes for employees, customers and partners. In this way, the business and IT serve internal and external customers’ needs to align to modern buyers and increasingly sophisticated expectations. The movement to transforming your business’s Data and analytics approach starts now.
 
Current Data Challenges
 
Companies today face an unlimited number of opportunities to enhance the business based on Data initiatives. By this point most people recognize that Data strategies can be the differentiator separating the good companies from the great companies. Building Data strategies that enhance the customer experience, provide future product or offering growth, streamline and improve operations and drive   employee innovation are critical to the future sustainability of every company.
 
Embracing these opportunities will not be possible if companies continue to think about Data from a traditional point of view. The traditional Data strategies of old will not scale and deliver value in the new Data world. To reach the full benefit that Data can deliver will require companies to overcome the challenges outlined below.
 
Massive Data Volume & Growth – The challenge is NOT driving Data growth but more so in keeping up with which Data to capture, store and analyze. Every business will benefit from the value that Data can bring; the key is choosing the greatest Data domain to invest time and energy into. Invest in the wrong domain and you will not receive the value you expect; or, invest in the wrong way and you will not get results that add value. Predictive and Cognitive Analytics can both add value to your business if they are applied successfully.

Real-time Reporting Challenges – Data is created, grows and accumulates in different ways and at different paces. Sensors create streams of Data that evolve constantly and can accumulate quickly to thousands of rows an hour. Customer purchase Data can also grow quickly, but once a transaction is complete, the record is achieved and will never change. Master Data can evolve overtime and reflects a point in time. And finally, Data that evolves over time has a changing dimension and can provide a view into changes over time. It’s critical to pull all these Data types into a single solution that is responsive to users’ needs.   

Slow response times of Data-driven systems – It is not surprising that with the huge amount of Data being reported on that processing and relevant access time is challenging. All the Data required to accomplish one’s goals once lived in a single Data center and that was normally owned by the company accessing it. Today that is far from the truth. Companies are pulling Data together that lives across the world; leveraging Data in both their own and third-party locations, and pulling information from cloud and traditional Data centers.

Securing Data – Weekly we hear about another Data related breach, leak or theft. Securing information, specifically traditional Data, is no longer a nice-to-have but a need-to-have function. This need is further complicated by the fact that not only does our Data reside in several locations, but our Data is also accessed by both our employees, customers and partners. Securing Data and access policies is a complex and ever-changing challenge as companies strive to provide open access to information while keeping control of the companies’ secrets.

Digital Transformation is changing the way companies create, curate, access and distribute information. The way a business interacts with itself and its customers’ needs to evolve to leverage quick and easy access to information which enables making informed decisions quickly. Data & Analytics strategies need to evolve to meet the needs of the Modern workplace.

Characteristics of Modern Data Strategies

Foundational - Data is at the heart of every business. Line of Business Applications, Customer Data, Partner Data and Public Data is being combined to provide the business answers to questions asked, or providing input when trends are be researched and discovered. A Modern Data strategy needs to consider all the Data domains required to drive the business forward over the next 20 years. There are five core functions of a Modern Data strategy. 1) Provide clean and accurate Data that is easily access. 2) Provide tools to user so they can build analytics to support the needs of the business without creating another version of the truth of corrupting Data integrity. 3) Allow Data to be analyzed so new trends can be discovered, vetted and confirmed or disputed. 4) Allow equipment to generate Data that is captured and combined with non-machine generated information. 5) Deliver and endless storage and computing capacity to support the needs of the business.

Ubiquitous - Data volume is growing and can be found everywhere. Master Data, Transactional Data, Social Data, email Data, Device Data and Image Data are being combined and leveraged for Research, Predictions and Historical review. Sentiments are being harvested from email history, product demand is being predicted based on online product views and social comments, customer behavior is anticipated based on Data from similar profiles and production schedule are combined with weather patterns to determine the best shipping locations. Never have companies had this high level of access to information to improve the business.

Availability - Data needs to be accessed in many ways and in most cases 24 hours a day. Employees, Customers and Partners need appropriate access to information to formulate traditional responses to questions and analyze Data for new trends and emerging insights. Data can no longer be locked and kept behind Data center doors. Data is the lifeblood of an organization; the appropriate people need access to the appropriate information on their terms. Master and transactional Data, industry information and third-party sources need to be quickly and easily pulled together to support customer and employee needs. Remote Workers, Global Partners and Local Customers depend on access to make better decision.

Secure - Data can be the most valuable resource a company has, and it can be the most vulnerable. Never has corporate Data been under seige at the level it is today—and the misconception is that you are the primary target. Many companies’ Data can be used as a bridge to their customers and their partner networks, and they won’t even know they were compromised. With companies sharing and opening up access to enable the business, they have to ensure they are not inviting unwanted access. Companies need to create and constantly monitor their Data strategies. Policies need to be put in place that both enable and curate their Data to support all aspects of the business and leverage constantly changing threats to insure their Data is protected.

Innovative - Consuming and understanding Data drives business success, but you must do all the hard work first; it’s the icing on the cake. There is no doubt that when a company gets to the point that they have accurate, secure and accessible Data, the sky is the limit. The ultimate goal is consuming Data for the sole purpose of driving better business outcomes. Whether that is your employees, customers or partners, the need is to provide Data that allows new insights to be discovered, customer Data to be positioned for a valuable services, or operational Data that drives partner efficiencies. Consuming the right Data makes the difference between a good company and a great company. Innovation comes a lot faster when people can focus on the creative aspect of innovating—not distracted by worry about Data availability and security.
 
Conclusion

The transformation of your business’s Analytics and Data strategy started yesterday. Are you already behind? There are three core phases every company needs to complete to have a Modern Data strategy. The first is a mission. I believe a company’s Data strategy mission needs to provide “All the Data and Information that employees, partners and customers need to enhance the designing, building, buying and consuming of a company’s product or service.” To build a plan that successfully delivers on that Mission, you need to set a series of goals with deadlines and deliverables.

These goals need to focus on building the data sources your company needs. Start internally with master data and transactional information, then incorporate unstructured data, move on to third-party data from partners and customers, and finally incorporate public domain information like weather, traffic, housing, birth rate, etc.

After you have the data sources pulled together in an accurate, secure and accessible manner, you can move into the third and final phase, Data consumption—again, the icing on the cake. With the Data sources available, Business Intelligence (BI) solutions can be used to build visualization to better communicate business conditions and trends, Analysis tools can be used to allow people to discover new insights, and Machine Learning (ML) or Artificial Intelligence (AI) tools can be applied to data to build entirely new statistics and outcomes that replace traditional spreadsheets builders and data analysts. With these three phases properly implemented, you will have a Modern Analytics & Data foundation to help drive your company’s success.
Author

Bill Topel

Bill Topel is Vice President of Sales & Marketing at Concurrency. Responsible for defining the strategic direction and operational management for Marketing and Sales.

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