Article | March 19, 2020
Business agility is the name of the game in 2020. Last year, the US-China trade wars gave business leaders around the world a preview of what it looks like when change and uncertainty become the new normal in the global economy—and for those caught flatfooted, it wasn’t pretty. Here we are nearly one year later and the world has changed dramatically once again. The trade war fiasco? That was just a dress rehearsal compared to what we are living through today with the recent outbreak of COVID-19. At times like these, few things matter more than having visibility into and the freedom to innovate with data to address the necessary business agility.
Article | April 30, 2020
In the present complex and volatile market with data as a nucleus, analytics becomes a core function for any enterprise that relies on data-driven insights to understand their customers, trends, and business environments.
In the age of digitization and automation, it is only sensible to make a move to analytics for a data-driven approach for your business. While a host of sources including Digital clicks, social media, POS terminal, and sensors enrich the data quality, data can be collected along various stages of interactions, and initiatives were taken. Customers leave their unique data fingerprint when interacting with the enterprise, which when put through analytics provides actionable insights to make important business decisions.
Table of Contents:
Business Analytics or Business Intelligence: The Difference
Growth Acceleration with Business Analytics
Business Analytics or Business Intelligence (BI): The Difference
Business Intelligence comes within the descriptive phase of analytics. BI is where most enterprises start using an analytics program. BI uses software and services to turn data into actionable intelligence that helps an enterprise to make informed and strategic decisions.
It’s information about the data itself. It’s not trying to do anything beyond telling a story about what the data is saying.
- Beverly Wright, Executive Director, Business Analytics Center, Georgia Tech’s Scheller College of Business
Some businesses might use BI and BA interchangeably, though some believe BI to be the know-how of what has happened, while the analytics or advanced analytics work to anticipate the various future scenarios.
BI uses more structured data from traditional enterprise platforms, such as enterprise resource planning (ERP) or financial software systems, and it delivers views into past financial transactions or other past actions in areas such as operations and the supply chain. Today, experts say BI’s value to organizations is derived from its ability to provide visibility into such areas and business tasks, including contractual reconciliation.
Someone will look at reports from, for example, last year’s sales — that’s BI — but they’ll also get predictions about next year’s sales — that’s business analytics — and then add to that a what-if capability: What would happen if we did X instead of Y.
- CindiHowson, research vice president at Gartner
A subset of business intelligence (BI), business analytics is implemented to determine which datasets are useful and how they can be leveraged to solve problems and increase efficiency, productivity, and revenue. It is the process of collating, sorting, processing, and studying business data, and using statistical models and iterative methodologies to transform data into business insights. BA is more prescriptive and uses methods that can analyze data, recognize patterns, and develops models that clarify past events, make future predictions, and recommend future discourse.
Analysts use sophisticated data, quantitative analysis, and mathematical models to provide a solution for data-driven issues. To expand their understanding of complex data sets, and artificial intelligence, deep learning, and neural networks to micro-segment available data and identify patterns they can utilize statistics, information systems, computer science, and operations research.
Let’s discuss the 5 ways business analytics can help you accelerate your business growth.
READ MORE: HOW TO OVERCOME CHALLENGES IN ADOPTING DATA ANALYTICS
Growth Acceleration with Business Analytics
1. Expansion planning
Let’s say you’re planning an expansion opening a branch, store, restaurant, or office in a new location and have accumulated a lot of information about your growing customer base, equipment or other asset maintenance, employee payment, and delivery or distribution schedule. What if we told it is possible to get into a much detailed planning process with all that information available? It becomes possible with business analytics. With BA you can find insights in visualizations and dashboards and then research them further with business intelligence and reports. Moreover, you can interact with the results and use the information to create your expansion plan.
2. Finding your audience
You’re right to examine your current customer data but you should also be looking into the customer sentiments towards your brand and who is saying what, and in what parts of the region. Business Analytics offers social media analysis so you can bring together internal and external customer data to create a profile of your customers, both existing and potential. Thus, you have prepared an ideal demographic, which can be used to identify people that are most likely to turn to your products or services. As a result, you have successfully deduced the area that offers the most in terms of expansion and customer potential.
3. Creating your business plan
The real-time interaction with your data provides a detailed map of the current progress as well as your performance. Business Analytics solutions offer performance indicators to find and forecast trends in sales, turnover, and growth. This can be used in the in-depth development of a business plan for the next phase of your thriving franchise.
4. Developing your marketing campaign
With Business Analytics, you’re capable of sending the right message to the audience most eager to try your product/service as part of a marketing campaign. You’re empowered to narrow down branding details, messaging tone and customer preferences, like the right offers that will differentiate you from the other businesses in the area. Using BA, you have gained a competitive edge by making sure you offer something new to your customers and prospects. It enables you to use your data to derive customer insights, make insight-driven decisions, do targeted marketing, and make business development decisions with confidence.
5. Use predictive insights to take action
With analytics tools like predictive analytics, your expansion plans are optimized. It enables you to pinpoint and research about the factors that are influencing your outcomes so that you can be assured of being on the right track. When you can identify and understand your challenges quickly and resolve them faster, you improve the overall business performance resulting in successful expansion and accelerated growth.
READ MORE: WHAT IS THE DIFFERENCE BETWEEN BUSINESS INTELLIGENCE, DATA WAREHOUSING AND DATA ANALYTICS
Article | August 13, 2020
The coronavirus outbreak in China has grown to a pandemic and is affecting the global health & social and economic dynamics. An ever increasing velocity and scale of analysis — in terms of both processing and access is required to succeed in the face of unimaginable shifts of market; health and social paradigms. The COVID-19 pandemic is accompanied by an Infodemic. With the global Novel Coronavirus pandemic filling headlines, TV news space and social media it can seem as if we are drowning in information and data about the virus. With so much data being pushed at us and shared it can be hard for the general public to know what is correct, what is useful and (unfortunately) what is dangerous. In general, levels of trust in scientists are quite high albeit with differences across countries and regions. A 2019 survey conducted across 140 countries showed that, globally, 72% of the respondents trusted scientists at “high” or “medium” levels. However, the proportion expressing “high” or “medium” levels of trust in science ranged from about 90% in Northern and Western Europe to 68% in South America and 48% in Central Africa (Rabesandratana, 2020).
In times of crisis, like the ongoing spread of COVID-19, both scientific & non-scientific data should be a trusted source for information, analysis and decision making. While global sharing and collaboration of research data has reached unprecedented levels, challenges remain. Trust in at least some of the data is relatively low, and outstanding issues include the lack of specific standards, co-ordination and interoperability, as well as data quality and interpretation. To strengthen the contribution of open science to the COVID-19 response, policy makers need to ensure adequate data governance models, interoperable standards, sustainable data sharing agreements involving public sector, private sector and civil society, incentives for researchers, sustainable infrastructures, human and institutional capabilities and mechanisms for access to data across borders.
The COVID19 data is cited critical for vaccine discovery; planning and forecasting for healthcare set up; emergency systems set up and expected to contribute to policy objectives like higher transparency and accountability, more informed policy debates, better public services, greater citizen engagement, and new business development. This is precisely why the need to have “open data” access to COVID-19 information is critical for humanity to succeed. In global emergencies like the coronavirus (COVID-19) pandemic, open science policies can remove obstacles to the free flow of research data and ideas, and thus accelerate the pace of research critical to combating the disease. UNESCO have set up open access to few data is leading a major role in this direction. Thankfully though, scientists around the world working on COVID-19 are able to work together, share data and findings and hopefully make a difference to the containment, treatment and eventually vaccines for COVID-19.
Science and technology are essential to humanity’s collective response to the COVID-19 pandemic. Yet the extent to which policymaking is shaped by scientific evidence and by technological possibilities varies across governments and societies, and can often be limited. At the same time, collaborations across science and technology communities have grown in response to the current crisis, holding promise for enhanced cooperation in the future as well.
A prominent example of this is the Coalition for Epidemic Preparedness Innovations (CEPI), launched in 2017 as a partnership between public, private, philanthropic and civil society organizations to accelerate the development of epidemic vaccines. Its ongoing work has cut the expected development time for a COVID-19 vaccine to 12–18 months, and its grants are providing quick funding for some promising early candidates. It is estimated that an investment of USD 2 billion will be needed, with resources being made available from a variety of sources (Yamey, et al., 2020).
The Open COVID Pledge was launched in April 2020 by an international coalition of scientists, lawyers, and technology companies, and calls on authors to make all intellectual property (IP) under their control available, free of charge, and without encumbrances to help end the COVID-19 pandemic, and reduce the impact of the disease. Some notable signatories include Intel, Facebook, Amazon, IBM, Sandia National Laboratories, Hewlett Packard, Microsoft, Uber, Open Knowledge Foundation, the Massachusetts Institute of Technology, and AT&T. The signatories will offer a specific non-exclusive royalty-free Open COVID license to use IP for the purpose of diagnosing, preventing and treating COVID-19.
Also illustrating the power of open science, online platforms are increasingly facilitating collaborative work of COVID-19 researchers around the world. A few examples include:
1. Research on treatments and vaccines is supported by Elixir, REACTing, CEPI and others.
2. WHO funded research and data organization.
3. London School of Hygiene and Tropical Medicine releases a dataset about the environments that have led to significant clusters of COVID-19 cases,containing more than 250 records with date, location, if the event was indoors or outdoors, and how many individuals became infected. (7/24/20)
4. The European Union Science Hub publishes a report on the concept of data-driven Mobility Functional Areas (MFAs). They demonstrate how mobile data calculated at a European regional scale can be useful for informing policies related to COVID-19 and future outbreaks. (7/16/20)
While clinical, epidemiological and laboratory data about COVID-19 is widely available, including genomic sequencing of the pathogen, a number of challenges remain:
1. All data is not sufficiently findable, accessible, interoperable and reusable (FAIR), or not yet FAIR data.
2. Sources of data tend to be dispersed, even though many pooling initiatives are under way, curation needs to be operated “on the fly”.
3. In addition, many issues arise around the interpretation of data – this can be illustrated by the widely followed epidemiological statistics. Typically, the statistics concern “confirmed cases”, “deaths” and “recoveries”. Each of these items seem to be treated differently in different countries, and are sometimes subject to methodological changes within the same country.
4. Specific standards for COVID-19 data therefore need to be established, and this is one of the priorities of the UK COVID-19 Strategy. A working group within Research Data Alliance has been set up to propose such standards at an international level.
Given the achievements and challenges of open science in the current crisis, lessons from prior experience & from SARS and MARS outbreaks globally can be drawn to assist the design of open science initiatives to address the COVID-19 crisis. The following actions can help to further strengthen open science in support of responses to the COVID-19 crisis:
1. Providing regulatory frameworks that would enable interoperability within the networks of large electronic health records providers, patient mediated exchanges, and peer-to-peer direct exchanges. Data standards need to ensure that data is findable, accessible, interoperable and reusable, including general data standards, as well as specific standards for the pandemic.
2. Working together by public actors, private actors, and civil society to develop and/or clarify a governance framework for the trusted reuse of privately-held research data toward the public interest. This framework should include governance principles, open data policies, trusted data reuse agreements, transparency requirements and safeguards, and accountability mechanisms, including ethical councils, that clearly define duties of care for data accessed in emergency contexts.
3. Securing adequate infrastructure (including data and software repositories, computational infrastructure, and digital collaboration platforms) to allow for recurrent occurrences of emergency situations. This includes a global network of certified trustworthy and interlinked repositories with compatible standards to guarantee the long-term preservation of FAIR COVID-19 data, as well as the preparedness for any future emergencies.
4. Ensuring that adequate human capital and institutional capabilities are in place to manage, create, curate and reuse research data – both in individual institutions and in institutions that act as data aggregators, whose role is real-time curation of data from different sources.
In increasingly knowledge-based societies and economies, data are a key resource. Enhanced access to publicly funded data enables research and innovation, and has far-reaching effects on resource efficiency, productivity and competitiveness, creating benefits for society at large. Yet these benefits must also be balanced against associated risks to privacy, intellectual property, national security and the public interest.
Entities such as UNESCO are helping the open science movement to progress towards establishing norms and standards that will facilitate greater, and more timely, access to scientific research across the world. Independent scientific assessments that inform the work of many United Nations bodies are indicating areas needing urgent action, and international cooperation can help with national capacities to implement them. At the same time, actively engaging with different stakeholders in countries around the dissemination of the findings of such assessments can help in building public trust in science.
Article | April 6, 2020
Today when we look around, we see how technology has revolutionized our world. It has created amazing elements and resources, putting useful intelligence at our fingertips. With all of these revolutions, technology has also made our lives easier, faster, digital and fun. Perhaps at a point when we are talking about technology, Machine learning and artificial intelligence are increasingly popular buzzwords used in modern terms.Machine Learning has proven to be one of the game changer technological advancements of the past decade. In the increasingly competitive corporate world, Machine learning is enabling companies to fast-track digital transformation and move into an age of automation. Some might even argue that AI/ML is required to stay relevant in some verticals, such as digital payments and fraud detection in banking or product recommendations.To understand what machine learning is, it is important to know the concepts of artificial intelligence (AI). It is defined as a program that exhibits cognitive ability similar to that of a human being. Making computers think like humans and solve problems the way we do is one of the main tenets of artificial intelligence.