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Project Management as a Core Competency

“Core competency” is a relatively young term introduced in the frames of economic theory by C. K. Prahalad and Gary Hamel. Core competencies can be described as the tools (skills/resources) helping to establish and ensure the competitive advantage.

Utility and Power Generation Industry is going through the slow but undeniable process of transformation. Smart energy is taking over the place of conservative services following lifestyle and technology development. That brings up a need for the new ways such as defining core competencies for existing strategy optimization.

The meaning of Project Management still stays underestimated way too often but for Utility and Power Generation industry plays rather important role. Wide spread net of procurement, production and supply require constant supervision and responsiveness.

Efficient Project Management ensures improved efficiency in delivering services, better flexibility enhanced customer satisfaction, opportunities for expansion, improved risk assessment and higher quality.

Remembering that competition within the industry is considerably high, benefits offered by the Project Management implementation are undeniable. Setting up Project Management as one of the core competencies for strategy optimization will provide better hotspot focus, reaching desired goals within specific time and cost frames.

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Logistics Through the Prism of Data

Logistics and optimization has been walking side by side for a very long time and there’s no evidence that the progress should turn into the excellence any time soon. Deepening of the world’s digitization dictates the deployment of data-driven optimization tools.

Mapping and tracking supply chain, warehousing administration – all it goes through the prism of data analysis.

Contemporary technology offers multiple software solutions and gadgets for everyday performance optimization.

Sensors installed to the warehouses’ gates, attached to the vehicles, are collecting and gathering data in order to enhance supply chain visibility and resilience drawing a complete picture of the ongoing processes. IoT implementation can be a great advantage improving warehouse ergonomics and optimizing the capacity.

The possibility to draw all the logistic indicators together into one dashboard opens new horizons for the logistic management. All in all, the minimization of the human factor and increasing automation of systems and structures bring great results.

Real-time management decisions are turning into beneficial basis for the overall supply chain development strategy. Data analysis helps not only to perform transportation management improvement but also helps to strengthen the supply security and enhance awareness of current circumstances (demand terms and volumes, external threats, etc.).

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Geographic Information Systems (GIS) for Offshore Wind Farms

Productivity, Cost-efficiency, Reliability and Sustainability – 4 floating grounds of the offshore wind energy. Renewable energy production is a young market and its development lies in the field of innovation applications.

A geographic information system (GIS) allows to visualize, question, analyse, and interpret data to understand relationships, patterns, and trends for current adjustments or further forecasting.

GIS role starts in the very beginning of a wind farm installation – the importance of GIS platforms for the planning of windfarms installation can’t be overestimated: any location which is being considered for the wind farm installation has very different offshore wind energy potential, roughness of the terrain and obstacles, road access, orography of the region, accessibility to transmission and/or distribution networks, soil conditions, environmental impacts [1]. In order to optimize the productivity and maximize the cost efficiency, offshore wind developers apply GIS software at the stage of geo planning.

GIS systems accompany the whole lifecycle of the offshore wind farm. Gathering operational data with geographical context provides an intuitive view of the operational landscape that enables immediate, location-aware, actionable decisions. It also enables improved operational planning, proactive asset management, asset tracking, reporting, and regulatory compliance [Esri]. Data collected through GIS platforms forms the trustworthy basis for the productivity planning and all related operations like scheduling the maintenance windows and performing all the necessary testing.

Thus GIS applications stay an irreplaceable tool for the whole offshore wind farm installation, operation and maintenance processes, providing multiple benefits the cost-efficiency and profitability improvement.

References: 1 “Geographic Information Systems (GIS) Application in Wind Farm Planning“ by Almoataz Y. Abdelazi, Said F. Mekhamer

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Subsea Cables Monitoring and Inspection. What’s New?

Cable monitoring & inspection process became an inseparable part of the Offshore Oil & Gas Industry’ performance from the very beginning – any gaps in sustainability and reliability of cable network might cause serious disruptions in producer’s activity which is already set under the pressure of the recent drop in O & G prices . Cable network laid deep under water is one of the most cost-generating sectors of the offshore projects, which makes it a subject for the continuous and progressing optimization.

Subsea cables are constantly exposed to variable threats so as axial compression, stress corrosion and fatigue, overheating of power cables, environmental changes, biofouling. So as all the operations connected to cable repair/replacement are considered to be increasingly complex and expensive, predictive maintenance seems to be the right way to handle possible inconveniences.

Predictive maintenance for subsea power and heating cables operates involves such measures as:

  1. Modelling of particular risk scenarios
  2. Temperature sensors installation/thermocouples
  3. Corrosion indicators installation
  4. Biofouling sensors installation
  5. Testing and inspection

Current innovative approach to predictive cable monitoring based on the implementation of integrated condition monitoring schemes, advanced coating and materials use in cable design, data accumulating tools for further analysis. Cable monitoring and inspection technology is progressively evolving following the software and gadget development heading for further and more complex optimization of cable networks.

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Supplier Management and Key Performance Indicators

According to Eugenio Filippi (Baxalta) an experienced supply chain manager (over 10 years across 2 industries), supply chain departments quite usually have a (large) number of measurements and scorecards in place, but somehow the Key Performance Indicators (KPI) seem to remain elusive.

Eugenio suggests to choose 5 most important (critical) indicators to represent your organizational performance and focus on them. These 5 indicators should be:

  • Manageable i.e. can be easily adjusted and updated on regular basis
  • Applicable to a cascaded-down management system where the up level of management might only look at 1 or 2 key indicators per each department, while the level below might have a much larger number of metrics drilling all the way down to the shop floor
  • Evident – easy to grasp and give a clear indication whether you are moving in the right direction.

The challenge includes not only the choice of suitable indicators – for the logistics / supply chain sector, what is often missing is the context in which these indicators should be used.

Regarding the indicator of volume/complaints ratio: Supplier1 might deliver 3,000 units a year and generate 3 complaints, while Supplier2 delivers 30,000 units and generates 30 complaints. Are they equally good/bad? You might need to look at what their Sigma level is (thus understanding how complex their processes are and how many opportunities for failure these generate) before you can answer that.  For instance, one might be delivering your products to 5 locations per given Tour, while the other to one central location only. So clearly the complexity of the process has to be taken under the consideration.

Very often departments have lots of measurements but since these have been around for years no one actually checks whether they are actually the right ones. All of the existing measurements have to be checked for the relevancy – some of them need to be adjusted to side factors (as in the example above), some of them are no longer applicable. Technical development should be included into the improvement process – current opportunities of data analysis and using IoT for Big Data gathering might be a great ground for establishing a sustainable KPI system for any organization.

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Biofouling of the Offshore Wind Farms – Origins, Threats, Elimination perspectives

Offshorewind energy cluster is gaining bigger energy market share through the latest decade. At the same time wind farms owners continuously face numerous challenges linked to operation and maintenance. And while some of these challenges are connected to “on the water” parts of the farm and relatively approachable for the solutions application, other challenges lie deep under the water. Among these challenges, the issue of biofouling can’t be ignored.

The term “biofouling” describes undesirable growth of marine organisms on immersed artificial structures. In case of the wind farms it concerns underwater cables, all the immersed parts of the substations and wind turbines. The biofouling formation occurs when free-floating planktonic organisms settle to form a biofilm which is growing through time becoming more and more complex and diverse through the colonization process.

Threats of extensive biofouling of the offshore wind turbines and substations include corrosion and metal fatigue increase with simultaneous lifecycle reduction, energy generation decrease. For the underwater cable systems biofouling means weight increase, growing hydrodynamic loads and distortions of the texture of the cable sheathing material. Thus the process of biofouling can dangerously affect all the subsea structures decreasing their productivity and cost efficiency.

Mitigation of biofouling processes stays the case of continuous research and innovative approaches application. Current measures against this process involve biofouling and corrosion sensors installation, mechanical grooming, cathodic protection, antifouling coating application. The research is aimed to improve existing antifouling measures, diminish interference with the marine environment and to develop preventive measures through the materials and design upgrade.

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Subsea Umbilicals – Challenges and Perspectives

Offshore and subsea Oil and Gas industry places the umbilicals as the main tool for establishing the connection between the host facility through which control is exercised, power transmitted and utilities such as injection chemicals delivered to subsea wells. Thus the umbilical technology stays a constant subject for research and improvement.

While the industry is exploring new depths, it’s setting up new requirements for the umbilicals -extensive length, amended reliability and sustainability, improved dynamics. Umbilicals developers face reasonable challenges meeting mentioned requirements: fluid pressure, tube stress, hold back tensions, effect of DAF, friction, track length, crush load, heavy inner bundles, stress utilisation, fatigue. All of these issues require constant improvements in umbilicals design and technology.

Current research trends are focused on deploying usage of lightweight corrossion-proof materials, sensor and monitoring applications installation for preventive meintenance, improving dynamics through the cable joints.

There are no doubts that umbilical technology will be evolving and gaining further importance along with the Oil and Gas industry heading to minimization of the Human Intervention into day to day processes.

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Supply Chain: Big Data Upgrade

“In God we trust; all others bring data.”   W. Edwards Deming

While world digitalization is picking up the pace, Big Data analytics is becoming more and more important tool in overall supply chain risk management.

Big Data analytics is based on algorithmic techniques, practices, methodologies, and applications in order to analyse and make sense of critical business data to improve understanding of operations and market. Analytics helps businesses to predict the likelihood of important events of any kind and to react timely with proper business decisions.

Most of supply chain executives consider big data analytics a disruptive and important technology, setting the foundation for long-term change management in their organizations.

Big Data can be characterised by 3 main features: Velocity, Variety and Volume.

Velocity. The fastest market player keeps the advantage. Rapid increase in the Big Data velocity supported by the continuous analytical software development allows to take considerably greater amount of crucial business decisions. Supply chain risks constantly require active reaction whether it’s about identifying types of risk, quantifying the impact, mitigating the risk or responding to the risk.

Variety. Different sources and different types of data provide diversified outcomes. Diversified outcomes lay the basis for developing versatile and agile supply chain management strategy.

Volume. Larger amounts of data allows analysts to predict the events with greater precision and likelihood thus creating more accurate and sustainable data models.

Therefore Big Data analytics is becoming inseparable optimization tool of the supply chain risk management providing such business benefits as:

  1. Big Data analytics undoubtedly improves business planning, demand forecasting, and supplier collaboration.
  2. Delivery networks might be efficiently optimized with the geoanalytics based on Big Data.
  3. Big Data is having an impact on organizations’ reaction time to supply chain issues (41%), increased supply chain efficiency of 10% or greater (36%), and greater integration across the supply chain (36%) [1].
  4. Embedding big data analytics in operations leads to a 4.25x improvement in order-to-cycle delivery times, and a 2.6x improvement in supply chain efficiency of 10% or greater
  5. Traceability and recalls are by nature data-intensive, making Big Data’s contribution potentially significant

As a result, Big Data analytics helps to build more wide, sustainable and reliable supply chain simultaneously mitigating, predicting and preventing the supply chain risks.

[1]“Big Data Analytics in Supply Chain: Hype or Here to Stay?” by Accenture


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Risk Management for Supply Chain: principles

“The biggest risk is not taking any risk… In a world that changing really quickly, the only strategy that is guaranteed to fail is not taking risks.”

 (Mark Zuckerberg)

In the constantly changing business environment the only thing that really matters is the ability to adapt to any diverse internal and external factors. Supply chain market sector certainly requires agile risk management strategy.

Supply chain risk management refers to the implementation of clearly laid strategies in order to minimize vulnerability and ensure continuity, through continuous risk assessment. Supply chain risk management is crucial since a small supply chain disruption from a localized event may have extreme economic consequences globally.

Supply chain risks are caused either externally or internally. External causes are those driven by events either upstream or downstream a supply chain. They involve supply and demand risks, the business and environment risks as well as physical risks. Internal risks are the ones driven from within the company. They include manufacturing risks as well as planning and control risks. There are various ways of managing supply chain risk.

A common process usually followed is the 6-step from Kiser and Cantrell:
1. Involving profiling the supplier base, identifies the essentials to the company and identifying each raw material for instance, affects the supplier base
2. Assessing the vulnerability of the supply chain, identification the scenarios that are likely to happen, why they would happen, and how it would cope with them
3. The implications of actions undertaken when decisions concerning a certain scenario are taken
4. Mitigation and it deals with the company setting goals and how to achieve them
5. Analyzing the costs and benefits of actions
6. Clarification of roles and responsibilities involving implementation of actions and measures

Following this simplified process might be taken as a ground base for developing sustainable risk management strategy in order to maximize the productivity and minimize the costs of the supply chain.

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