Self-service data visualization and exploration, a growing trend

Executives will gain advantage by moving beyond simply knowing what happened to preemptively understanding the forces acting on their business.

1. The economic crisis determined the private companies and even the public sector to significantly adjust and to look for efficiency solutions. How have the IT&C sector in general and SAS Romania in particular, contributed to the efficiency increase?


As ANALYTICS is in our DNA, efficiency topics are natural to SAS and we have always been preoccupied with developing software that helps our clients manage their problems.

The utilities industry is investing heavily in large-scale smart meter implementation projects, creating a new flood of data that must be harnessed, converted into information and used to build more efficient operations. The deluge of data will offer utility forecasters many new opportunities to optimize resource allocations, predict future growth and deepen insight for the utility planning process. The ability to predict the volume, magnitude and location of demand – along with improved revenue projections – will bring significant financial rewards to companies that successfully glean predictive insight from their data.

Our competence has helped our customers both in the commercial area and in manufacturing quality.

In the commercial area, we offer Demand Forecasting, which helps harness the power of the data coming from investments in AMI and Smart Grid to improve forecasting. Moreover, it enables the user to sense demand signals, shape and predict demand more accurately. To this purpose, we provide solutions for Finance and Operations, Asset and Operations Optimization, Marketing, as well as Energy Trade and Risk Management.

A second very important area for us is Manufacturing Quality. Quality has many definitions, but the most important one is not conformance to specifications, the extent to which a product provides superior service, or the features included in the product. When it is time to make a purchase decision, the customers' perceptions trump all of those definitions. In an environment where product recalls, government intervention, and lawsuits are front page news, customers are starting to question brands that seemed to have been beyond reproach. We are enhancing our partner’s ability to monitor, measure, and manage those perceptions that have significant impact on the ability to detect field issues, differentiate products, and increase profitability. In this respect, the solutions we offer are: Customer-Driven Quality, After-Market Service and Service Revenue Optimization.


2. Is the Romanian public administration aware of the need for IT&C solutions in order to increase the efficiency of long-term expenditures, as well as of short-term results? What are the indicators/ tendencies for this? Please detail.


Yes, the Romanian public administration is aware of their need for IT&C solutions. The majority of Romanian customers use traditional Business Intelligence (BI) tools that are extremely good at tracking raw transactional numbers like sales or collection figures. What they fail to adequately address are the root causes, or drivers, of trends in those numbers. Moreover, they are typically able to tell what happened – but not explain why (unless it is evident in some other numeric data), let alone alert the business as a change emerges. Executives will gain advantage by moving beyond simply knowing what happened to preemptively understanding the forces acting on their business, and further real time decision will play a bigger and bigger role.

Answering questions like – What is causing a delay of payment from our largest customer? Why are sales/ collection in the southwest region down? How is user sentiment impacting our newest product? – with the average BI tool is challenging: at best, it takes a great deal of time to gain even one additional level of insight. The cost of these investigations is often high. Large numbers of IT staff must collaborate to extract, transform and load the data into a warehouse, update data dictionaries and then reconfigure the layers of OLAP, summarization, reporting and dash boarding.

To provide greater value, information access tools must evolve in two ways. They must enable users to answer deeper, sometimes ‘fuzzier’ questions about the enterprise. Then they must make it possible for general business users to easily obtain information.

Deeper questions require more thought than usual. In the enterprise, more thought translates to more content. So the first challenge is to gain access to more information – including unstructured content like emails, documents and PDFs – breaking down digital silos throughout the enterprise and integrating the content together. The downside is that this is a challenging activity because mapping unstructured data into structured storage can be exhausting. A combination of entity extraction, automated sentiment analysis and social network analysis might just turn up the problem account, internal resource or impossible customer requirement. The structured data leads the way, identifying the transactional problem, complemented by the unstructured data, which fills in the underlying cause.



3. How has the business intelligence perception evolved in 2015? What are the expectations for 2016?


Business intelligence has evolved into self-service data visualization and exploration. Business users demand more flexible and powerful access to the data that is available in the organization without having to rely on IT for finding answers for their questions. IT is transforming more into an enabler for agile self-service data analysis rather than a provider of answers.
Gartner now talks about the emergence of citizen data scientists, users who require self-service data access and flexibility in ways to visualize and explore the data in order to answer business questions. They also predict for the near future a significant growth of that type of user in organizations, actually, they predict that the number of citizen data scientists in organization will grow 5 times as fast as the number of data scientists.

In the future, this new generation of citizen data scientists will demand self-service integrated data exploration and discovery environment that allows them to easily apply the right technology to find answers to business questions quickly and with high confidence. We also expect that this new generation will demand more powerful analytical tools to be able to drill deeper into large volumes of data in order to answer more complex questions. The reliance on highly specialized data scientists will become a bottle neck if organizations do not invest in strategies that allow them to expand their analytical talent pool and empower the citizen data scientist.


4. From your point of view, which industry has registered the fastest growth in 2015 by using efficient IT&C solutions? Were you surprised by any of the industries? Please detail.

Financial services is always a leader in the application of new technologies. Many financial services organizations are looking into the potential of utilizing data they can collect for addressing many different business problems. For example, reducing costs though more accurate fraud detection solutions based on utilizing new data sources. Related here is the topic of cybersecurity to reduce exposure to cyber-attacks and stop fraud before it occurs. Cybersecurity is also becoming a hot topic for many other industries, especially government, communication, and retail.

Financial institutions are also leaders in leveraging data from online and mobile customer applications for internal and external value creation. Internal value creating might provide more context for relevant personal marketing to customers on their mobile devices when they use the online banking application. External value might provide customer behavior data to merchants and partners to help to improve their marketing.

In many organizations, we have seen large interest in the potential of the internet of things. Insurance companies are looking into more usage-based premium pricing for car and health insurance based on data analysis of telematics devices and wearables. Insurers will gain better consumer insight, improve CRM, generate more accurate pricing and have a more predictable risk base. Energy and transportation, manufacturing companies are looking to leverage the new opportunities for more efficient network capacity management, predictive maintenance and operational process improvements.
We were not really surprised by any of the industries.


5. BIG data is the new BIG oil. How does SAS help monetize this new fact?

SAS provides solutions to many organizations in different industries that want to monetize big data. This applies to organizations utilizing their own data in combination with new external data, such as textual data from social media platforms (Twitter, Facebook, LinkedIn), website logs and geo-spatial data from mobile devices for better customer services and more targeted product offers. Other organizations are looking into providing value-added services based on the data they collect, such as call center organizations, collection agencies, public internet providers.

For example, ZAPFi helps organizations by providing sophisticated personalized marketing through its free Wi-Fi hot spots, called ZapFi Zones.

An energy company uses SAS to monitor real-time data from their remote devices to constantly apply analytical models which can automatically identify anomalous episodes in the data that might lead to failures and expensive downtimes.


6. Do the customers fully acknowledge the real needs and the real instruments for growth? How do you see this perception in terms of the customers’ budgets?

SAS prospects are always looking to get more value out of their data repositories. With Big Data, these repositories are growing beyond anything we have seen before because of new data storage and management technologies, such as Hadoop. Even though there is a new scale of the economy for storing data with this new technology (there are statistics that claim that storing data in Hadoop is by an order cheaper than storing data in traditional database systems), the real value lies in the insights that can be gained from these data repositories. More and more organizations are starting to realize this and are investing in big data analytics. However, they also realize that technology alone is not the answer, they need to identify the business case and implement the organizational structure to become a data-driven organization.