Success at Work through the Power of Analytical Thinking
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Success at Work through the Power of Analytical Thinking
- 1. Success at Work through the Power of Analytical Thinking Presented by Sharala Axryd, Founder and CEO The Center of Applied Data Science
- 2. WHO ARE WE? • We are CADS, aims to make the world more self- sustainable through technology, insights and intelligence. • With that aim in mind, we educate our clients on data management, integration and analysis. We put customers first, and aim for our customers complete independence from us and our services at the earliest possible window. We empower clients so they can be robust, agile and ready to face tomorrow’s world.
- 8. Crucial 21st Century Skills Soft Skills Instrument Analytical Thinking Open-mindedness, Creativity Openness Conscientiousness Proactivity Learning Styles: a. Analytic/Logical b. Factual/Practical c. Abstract/Theoretical Assertiveness Flexibility Adaptability Decision-Making Style: a. Rational b. Intuitive c. Avoidant d. Dependent Ways of Knowing: a. Knowing with the help of others b. Knowing on their own Teamwork People skills: Understands Strengths and Weaknesses and uses them accordingly, Empathy Communication Skills
- 9. Training for soft skills is the #1 priority for talent development in 2018 - LinkedinWorkplace Learning & Development Report 2018
- 10. 2018 Workplace Learning Trend
- 14. The effective use of digital technologies in the oil & gas sector could reduce capital expenditures by up to 20%; cut operating costs in upstream by 3-5% and by about half that in downstream. Source: McKinsey
- 16. According to an Accenture workforce study, nearly 70 % of energy leaders surveyed believe that their industry will be completely transformed by intelligent technologies AI skills are among the fastest-growing skills on LinkedIn, with a 190% increase in AI skills on LinkedIn from 2015 to 2017.
- 18. “The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.” — Alvin Toffler, American Writer, Futurist, Businessman
- 19. Connect With Us @thecads.org info@thecads.org The Center of Applied Data Science @thecadsmalaysia
Editor's Notes
- Culture starts with what people do and how they do it. In any industry, what people do may not differ dramatically, but high-performing organizations distinguish themselves in how they do it. This cumulative effect of what is done and how it is done ultimately determines an organization’s performance. Culture also encompasses why people do what they do. As the Titanic’s captain grasped a little too late on that fateful night in 1912, 90 percent of an iceberg’s mass lies beneath the surface. Culture is similar as it includes observable behaviors (the what and how above the surface) as well as everything underneath – the shared mindsets and beliefs that influence how people in an organization behave. Just like a captain navigating frigid waters, anyone trying to understand an organization’s culture must recognize that most of what matters cannot be readily seen. Culture correlates with performance. Based on McKinsey’s research of over 1,000 organizations that encompass more than three million individuals, those with top quartile cultures (as measured by our Organizational Health Index) post a return to shareholders 60 percent higher than median companies and 200 percent higher than those in the bottom quartile. Healthy cultures enable organizations to adapt. In a world where the one constant is change, culture becomes even more important because organizations with high-performing cultures thrive on change. The converse also holds true: Unhealthy cultures do not respond well to change. McKinsey research shows that 70 percent of transformations fail, and 70 percent of those failures are due to culture-related issues. The Cost Of Toxic Employees Research conducted by Dylan Minor and Michael Housman from the Kellogg School of Management at Northwestern University found that roughly one in 20 workers were ultimately fired for toxic behavior. The study also found that avoiding toxic hires can save companies about $12,800 in turnover costs. These are costs that can be reinvested into growing and cultivating other members of the organization who add tangible value creation.
- Critical thinking dictates that these wants do not have very much priority in the reasoning process. Many people begin the analytical reasoning process with the desire to make that particular want a part of the final decision and that desire often makes the entire analytical reasoning process invalid. If you take a new job based on a want for more money to play with and find you really hate the job because it takes a lot more of your time than the one you liked but left you have probably made the wrong decision based solely on your desire for more money. As an example, consider that you have decided to buy a new house, and have narrowed the choices to two. One you really like and want, but it is more than you can afford, will require a 50 mile commute to work and needs a new roof. The second choice is less desirable, and after seeing the first you don't really want it, but the commute is short, it is affordable and needs no repairs. Reasoning with your wants, you decide that the first house is the way to go; the commute is only 20 minutes longer (if you drive 100 mph), you will save money somewhere to pay for it (with no idea just where that might be) and somehow don't see the roof at all. You have now decided to buy the house using faulty reasoning. Your decision is based on lies to yourself (driving 100 mph indeed!), ignoring consequences of your actions (no more of the eating out that you enjoy so much) and intentional blindness (the bad roof doesn't exist). By using truly critical and analytical thinking on the other hand, you decide to make a 50 mile commute to work each day for a week (test the hypothesis that it's OK) and discover you don't like it at all. You make a serious budget and find that all your entertainment must disappear to afford the new house and you don't ignore that fact but rather consider the consequences seriously. You get a ladder and take a hard look at the questionable roof, and realize it will cost an additional $5000 to fix it. Final conclusion; house #1 is not for you in spite of the fact you really want it. Your wants have not been allowed to interfere with your critical reasoning process and you will be happier for it. You have correctly analyzed your problem, using all the data available, testing new procedures or theories, and you have not conveniently forgotten or ignored anything in order to produce the answer you want. You may dream of house #1 for months afterward, (and may eventually find one you like just as well) but you have made the right choice for you and will understand that in a few days when the disappointment fades some.
- Top Five Analytical Skills 1. Communication Having strong analytical skills means nothing if you cannot share your analysis with others. You need to be an effective communicator who can explain the patterns you see in the data. Sometimes you will have to explain information orally in a meeting or presentation. Other times, you will have to write a report. Thus, you need to have both strong written and oral communication skills. Enhancing group productivity Interpersonal Listening Reporting Streamlining processes Surveying Teamwork Verbal Communication Written Communication 2. Creativity Often, analyzing requires a creative eye to spot trends in the data that others may not find. Creativity is also important when it comes to problem-solving. Employees often must think outside of the box to come up with effective solutions to big problems. Budgeting Collaborating Improving MATLAB Optimization Planning Predictive modeling Problem-solving Restructuring Scatter plots Strategic planning Synthesizing 3. Critical Thinking Critical thinking is necessary for having strong analytical skills. Critical thinking refers to evaluating information and then making a decision based on your findings. Critical thinking is what helps an employee make decisions that help solve problems for the company. Auditing Benchmarking Big data Business intelligence Calculating Case analysis CATWOE Causal relationships Classifying Comparing Computing Correlation Counting Decision making Deductive reasoning Diagnosis Dissecting Evaluating Financial management Financial recording Identifying cost savings Inferential statistics Interpreting Judgment Logical thinking Prioritization Reasoning Risk assessment Troubleshooting 4. Data Analysis No matter what your career field, being good at analysis means being able to examine a large volume of data and find trends in that data. You have to go beyond just reading and understanding information, to making sense of it, and seeing patterns. Business analysis Case analysis Cost analysis Credit analysis Critical analysis Descriptive analysis Financial analysis Fourier analysis Fundamental analysis Heptalysis Industry analysis Loglinear analysis MOST analysis Multiway data analysis Pacing analysis PESTLE analysis Policy analysis Predictive analytics Prescriptive analytics Principal component analysis Bivariate analysis Price-earnings ratio Price-earnings to growth SAS Process analysis Qualitative analysis Quantitative analysis Return on investment (ROI) Rhetorical analysis Scenario analysis SCRS analysis Sentimental analysis Social analysis SPSS Statistical analysis Structured data analysis SWOT analysis Technical analysis Univariate analysis Cohort analysis Comparative analysis 5. Research Often, an employee has to first collect data or information before analyzing it. After all, you must learn more about a problem before solving it. Therefore, an important analytical skill is being able to collect data and research a topic. Investigating Metrics Data mining Data collection Prioritizing Recording facts Taking inventory Checking for accuracy
- The oil and gas industry has gone through serious changes in the last fifty years or so. Methods of exploration, technologies, environmental regulations, and radical volatility in commodity markets have combined to alter the face of an entire industry. One thing that hasn’t changed, however, is the need for certain skills from anyone who hopes to find work in this exciting field. Oil and gas companies are constantly searching for workers who can help them meet the challenges of the ever-changing terrain within their industry. What’s changed? Put simply, analytics tools and techniques have advanced far and fast—to the point where they can unlock the production potential of complex process facilities and enhance asset investment returns in O&G. Applied properly, advanced analytics can yield returns as high as 30-50 times investment within a few months of implementation. Moreover, they can positively transform the organizations and fundamental operating models of O&G production systems.
- “In a gentle way, you can shake the world.” —Gandhi Are you prepared for a career in the 21st century? If you’re not sure, you might want to rethink your next steps. According to the World Economic Forum, five years from now, over one-third of skills (35%) that are considered important in today’s workforce will have changed. By 2020, the Fourth Industrial Revolution will have brought us advanced robotics and autonomous transport, artificial intelligence and machine learning, advanced materials, biotechnology and genomics. The idea is to develop a tool that could assess the soft skills of data professionals but also give us the opportunity to use it for the assessment of soft skills of other types of employees as well. This includes many of the crucial employee 21st century skills, for example: ways of thinking (critical thinking mainly), communication, collaboration, creativity, ways of working (plan and prioritise work mainly), adaptability, etc. This is an initial pool of skills that we could test and see how they work. We could add more skills if we think there are more skills crucial for employees that we could test. So, in other words we try to develop a soft skills instrument, like a personality instrument, that measures different aspects of the personality and soft skills of employees that could be used in any industry. The next step is to gather data from professionals in order to identify skills dimensions (just like the EDGE instrument) and employee profiles. We have two aims: 1. The first aim is to test data professionals and try to identify profiles of data professions, for example which skills are prevalent in data professionals. In this sense, we could develop a use case around the crucial soft skills of data professionals. 2. The second aim is to start using it to different types of employees and identify how they perform on the identified soft skills. It could be used in employee recruitment and selection and later in team building. In team building it could be used as a tool that identifies employee profiles and helps in the development of teams with supplementary ways of thinking and working. But that could be done in a later stage when we manage to gather and analyse more data.
- Soft skills are taking the spotlight in workplace learning. The World Economic Forum (WEF) have predicted a significant rise in demand for soft skills by 2020. This means that soft skills such as problem-solving, cognitive abilities and social skills will be sought after, by up to a staggering 36% more. This anticipated growth in skills demand can be linked to several factors, including new technologies such as Artificial Intelligence slowly taking over more technical roles, and the quickening pace of organisational change leading to a greater need for resilience and the ability to lead during times of uncertainty. With less than two years to go, it’s likely you are already starting to notice a shift in demand for soft skills training in your organisation. In fact, according to LinkedIn’s Workplace Learning Report, training for soft skills is already the #1 priority for 2018. Organisations able to perform in areas such as communication, collaboration and emotional intelligence are likely to experience two times the growth, profitability and success compared with organisations lacking in those areas. Similarly, soft skills are what separate average performers from high performers. They are crucial for employees, managers, supervisors and leaders looking to improve performance and get to the next level in their careers. Stanford Research Institute reported that 75% of long term job success depends upon soft skills mastery and only 25% on technical skills. Communication – good or bad – has a massive impact on the overall performance of a business. A recent study showed that 70% of the workforce is unengaged, and a lack of internal communications is a key reason why. Communication also has a massive impact on productivity - teams with good communication skills are on average 20-25% more productive.
- In today’s dynamic world of work, the path to opportunity—for both individuals, and organizations—is changing. The short shelf life of skills and a tightening labor market are giving rise to a multitude of skill gaps. Businesses are fighting to stay ahead of the curve, trying to hold onto their best talent and struggling to fill key positions. Individuals are conscious of staying relevant in the age of automation. Enter the talent development function—the organizational leaders creating learning opportunities to enable employee growth and achievement. They have the ability to guide their organizations to success in tomorrow’s labor market, but they can’t do it alone. That’s why we surveyed approximately 4,000 professionals globally on LinkedIn with the goal of providing a holistic view of modern workplace learning. All parties agree, the #1 priority for talent development in 2018 is training for soft skills. Each group in our survey—from executives to managers to talent developers—identified ‘training for soft skills’ as the #1 priority for talent development in 2018. In the age of automation, maintaining technical fluency across roles will be critical, but the pace of change is fueling demand for adaptable, critical thinkers, communicators, and leaders. As technology accelerates, soft skills are in high demand to fuel people and business growth.
- Today, the top companies around the world use data to make decisions about their business. The reason they’re leading the way is that they’ve gained a strategic advantage over their rivals simply by shifting their focus to data rather than relying on business acumen alone. Fewer top-performing companies (40%) than laggards base the majority of their business decisions on gut feel or experience (70%). In other words, more organizations that make data-driven decisions are at the top of their game than businesses whose decisions are driven by instinct. Let Data-Based Lessons Shape Your Business Becoming a data-driven organization is a little more difficult than waking up one morning and deciding to use data to drive your business decisions. And it’s not just about selecting the best analytical tools that will help you derive insights from data, although of course, it helps to have the right technology architecture in place. It’s about realigning your organization’s culture to make sure that everyone knows the value of the data – and how to make the most of it. Change has to come from the top, and transforming company culture means getting leadership on board. The best way to get leadership to sit up and take notice is by showing how analytics will bring value to the organization. As you begin applying those insights directly to the business, using them in the decision-making process will start to become embedded within the organization.
- A recent PwC report found a clear correlation between innovation and success in growing revenues across industries. In breakthrough innovation and growth, they report that over the past three years, the most innovative 20% in the study grew at a rate 16% higher than the least innovative. And in the span of only five years, the top innovators forecast that their rate of growth will further increase to almost double the global average, and over three times higher than the least innovative. “By leveraging innovations like smart data analytics, big oil has the potential to save billions. Companies will save by having data that’s accessible throughout an organization, not siloed by departments. They can leverage this information to pump by exception and in return, see a reduction in downtime.” Companies will save by having data that’s accessible throughout an organization, not separated by departments. They can leverage this information to pump by exception, and in return, see a reduction in downtime. As global demand for oil continues to rise America’s shale fields generate a vast new supply, have more access to better data analytics has never been more crucial to the industry. “Startups are built on vision, and it’s imperative to keep it steady and a bit nimble. Markets shift rapidly (in our industry, the price of oil can go drastically south), and moving flexibly to shift execution pace became necessary to make our product successful in the long haul. With software that improves quality of analytics, it creates confidence within the operation for those on the front lines to make decisions. Being disciplined with big data means you get accounting, production and budget systems all communicating effectively.”
- A problem space is a set of goals for a creative process. Problem spaces do not include any details of the solution. By starting with a problem space, creative processes avoid making assumptions about the solution that eliminate possibilities too early. Understand stage Trying to have intent observations with a childish curiosity, not just paying attention to what the stakeholder says, but paying attention to actions actively listening to what wasn’t expressed to have insights into the thoughts and feelings. It is easier said than done though. Define stage Explore the problem space before thinking about the solution Contrary to the traditional approach where the proposition starts with a solution in mind, Analytical Thinking is based on exploring the problem space first, before even thinking about a solution. Using divergent thinking first to explore all the different perspectives about the stakeholders and their context, bring a common understanding of stakeholder and define the problem that needs to be solved using convergent thinking. This helps in answering the “Why” of the initiative before thinking about “How” and “What”. Ideate stage Collaboration with diverse perspectives to ideate Bringing key stakeholders from different lines of businesses, expertise, experience levels and backgrounds together in one room and facilitating an environment where judgments are deferred to bring as many ideas out as possible. This again highlights the importance of diversity of ideas for ideation before using convergent thinking to select the best ideas for possible solutions. Prototype stage Prototype not plan Another key aspect of Design Thinking is its bias towards action. Instead of talking about the concept to death, building a prototype is required. A prototype could be as simple as a sketch on a piece of paper or as complex as a mockup using design tools on a computer. The whole idea is that as you prototype, you see how the solution might actually be used in real life. It also reduces the need to invest tremendous resources to get user feedback. Test stage Get feedback from key stakeholders at each stage They beauty of this approach is to involve the user / key stakeholder throughout the design cycle. Not just obtain feedback from the user on the prototype, but even involving the users in coming up with ideas and prototyping. Show (not tell) how a solution might look like for them and get feedback with an open mind. At this point, also obtain feedback from business and technology / operational side to ensure the idea is both viable and feasible. Iterate And finally, be ready to fail and try again. The advantage of this approach is that, you’ll know fairly soon whether your solution direction is on the right direction, unlike the traditional approach where user is the last to have a glimpse at the solution. Fail early, fail fast. Analytical skills are important for: gathering information and reporting solving complex problems making well-informed decisions summarising statistical data identifying trends streamlining processes executing projects effectively
- In 2017, Petronas’ capital expenditure was RM44.5 billion. By effectively using technologies like analytics, data science etc, Petronas’ capital expenditure could be reduced to RM35.6 billion Source: http://www.theedgemarkets.com/article/petronas-raises-capital-expenditure-rm55-billion A tech-driven oil field is already expected to tap into 125 billion barrels of oil and this trend may affect the 20,000 companies that are associated with the oil business. Hence, in order to gain competitive advantage, almost all of them will require data analytics to integrate technology throughout the oil and gas lifecycle. With the use of big data, companies can not only cut costs but also capture large data in real time. Such use of analytics can help in improving production by 6%-8%. However, the role of big data in the industry of oil and gas goes beyond efficiency and analyzing large volumes of data in real time. Near-real-time visualization, storage of large data sets and near real-time alerts are considered the most important advantages in big data analytics. In a recent survey by Accenture and Microsoft, oil companies and those in the support industries established that 86% to 90% of respondents said that an increase in their analytic capabilities, use of mobile technologies in the field and banking more on Industrial Internet of Things would increase the value of their business. According to the survey, over the next 3–5 years, investment in big data and automation are expected to increase from 56% to 61% and 53% to 65%, respectively. Finding and producing more hydrocarbons, at lower costs in economically sound and environmentally friendly ways can not only add value to the data but also helps in accurate decision-making.
- As oil industry generates a humongous amount of information, big data analytics holds the potential to transform this sector. With the help of big data analytics, oil companies receive real-time information about processes. This real-time information assists authorities to take effective decisions that can assist them in enhancing production. Real-time insights provide the firms in keeping track of operations and track what can go wrong leading to a mishap. Big data analytics is changing the oil and gas industry by giving them actionable insights on what location is the best for drilling. Analytics provides organizations insights on how and where to usethe drill. The actionable insights are considered to be a boon for the oil and gas industry. With these insights, authorities can take a call on what can be done to avoid the damage or reduce downtime of the high maintenance machinery. Big data analytics has numerous applications for everyone in every aspect of life. With such assistance from analytics, authorities should now focus on ways through which they can leverage this technology. Apart from finding ways, CTOs and CIOs can also focus on methods of training their employees to work on the software that helps in gaining actionable insights. Hiring people who are experts in the field of big data analytics can also assist companies in leveraging this technology. What we declare to be AI will be a work in progress for some time. But trend lines suggest that we will continue to advance computing to process those other cognitive skills and we will continue to be surprised at the level of cognitive processing in species other than humans. Meanwhile, AI is already having three pretty dramatic impacts on oil and gas: First, in the upstream, AI is being applied to subsurface data and, through better interpretation of that enormous trove of data, petroleum engineers are confidently expanding the amount of oil and gas that is recoverable. Second, AI is helping reduce demand for fossil fuels by transforming transportation markets. Finally, AI is reducing costs and improving productivity throughout production, midstream and downstream.
- Big Data Analytics is a new ball game for a lot many industries but not for the oil and gas industry. This industry has, for the longest period of time, dealt with large volumes of data on which they are heavily reliant to make their business decisions. For instance, let’s take up an issue that drives 3.5 percent of the world’s GDP – ‘Corrosion’. It has a huge economic impact on all types of infrastructure. Corrosion also poses a threat to human safety, disrupts industrial operations and can cause major environmental damages. Fundamentally, corrosion is the deterioration or destruction of metals and alloys in the presence of an environment by chemical or electrochemical means. It is a major cost section with over US$2.2 trillion being spent on it globally every year. Pipelines are the safest and the most efficient way to transport energy. Crude oil, natural gas, petroleum products are transported through thousands of kilometers of pipelines across the world. Most of the times, pipeline failures are prevented by evaluating, inspecting and maintaining the assets through integrity management. One such component of this management is in-line inspections. Thickness gauges and other tools commonly knowns as ‘smart pigs’ are used to conduct these inspections. These devices are inserted into the pipelines such that the fluid flow within is not disturbed. Corrosion or cracks that could lead to explosions, leakages or ruptures can be assessed using these devices. The devices and sensors generate vast volumes of data in varying formats and with varying degrees of accuracy. With analytics used on the data, a trail or pattern can be formed thereby easing out maintenance regimes and risk management.
- If a new World Economic Forum (WEF) report is to believed, emerging tech will create more jobs than it destroys. At least for the next four years. Specifically, The Future of Jobs Report 2018 predicts the loss of 75 million jobs by 2022, and the creation of 133 million jobs over the same period, for a net increase of 58 million jobs. That’s obviously good news, but this extraordinary swing in jobs will pose a challenge to both employers and workers. For employers, it means making the right investments in technology; for workers, it means acquiring the right skills. “By 2022, everyone will need an extra 101 days of learning.” A whopping 54 percent of all employees will require “significant” training to either upgrade their skills or acquire new skills altogether. Of these, 35 percent will require an additional six months of training, 9 percent will require training lasting six to 12 months, and 10 percent will need more than a year to upgrade their skill set. By 2022, “everyone will need an extra 101 days of learning,” according to the WEF. Nearly one in four companies said they’re undecided or unlikely to pursue the retraining of existing employees. Two-thirds of employers expect their workers to either adapt or pick-up skills as their jobs evolve. Anywhere from half to two-thirds of companies said they’ll just resort to hiring contractors, temporary staff, and freelancers to address any deficiencies in work skill.
- A college degree at the start of a working career does not answer the need for the continuous acquisition of new skills, especially as career spans are lengthening. Vocational training is good at giving people job-specific skills, but those, too, will need to be updated over and over again during a career lasting decades. – The Economist Fortunately it doesn’t take much time or money to boost your skills to make you more competitive. You just need to have a strategy for ensuring that your knowledge and skills are always up-to-date. Even if you aren’t in a technical job, technical skills like software and social media help everyone. Creative skills like graphic design and photography are also useful in a variety of jobs. Skills like project management, team leadership, and conflict resolution are critical to anyone’s success. In short, knowledge work is an area that will continue to grow; career options will become more varied and require ongoing education to remaining current.