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Digital Innovation Drives New Business Models In Mining Industry

Ruediger Schroedter

The increase in digital technologies is playing a critical role in mining operations. Smart products are guiding this revolution in how mining firms think about business models.

The mining industry faces several hurdles today, according to IDC. Commodity prices have dropped almost 50% from recent highs. Capital needs and a shortage of talent are driving up operating costs. Productivity has fallen by 3.5% annually over the past decade.

A new frontier

The transformation in mining has begun. (If you’re not sure what exactly that means, see What is Digital Transformation?) Big Data propels faster decision-making. Robotics improve safety and yield. Smart products transmit loads of data. Backroom procedures and reporting are completed in real time.

The new mining business models embrace these changes. The potential improvements and productivity gains are expansive. These models rely on real-time information and collaboration like never before.

As a result, new models are grounded in three areas. For one, mining is becoming more predictable. Second, the industry is more collaborative across the supply chain. Third, automation opens up new markets and yield.

Bonus: Click here to learn more about Digital Transformation in Mining

What’s driving change?

The digital drivers of these new models fall into two main categories. The first is the rise of the Internet of Things. (Learn more about the meaning – and opportunity – behind the Internet of Things.) These smart devices are equipped with sensors, software, and wireless tech. The devices can connect with each other and detect, store, share, and send data.

The second is the rise of Big Data. Collection and storage of massive amounts of data is manageable with cloud systems and lower storage costs.

Integrated systems can analyze and report on this data in real time. Data from varied processes are tied together like never before. Decisions are better informed and made faster.

Let’s examine the three core ways mining business models are shifting.

1. Predictable production

In a digitally connected mining environment, the components are deeply integrated.

Imagine a firm where internal departments, shippers, customers, and vendors collaborate from a shared set of data. Documents are exchanged easily and are shared centrally. Some connected machines share data with robust databases. Data from other internal systems combine with production data to create new models. Competitors’ demand and supply data is overlaid.

All this data helps your mining company predict sales and production with more accuracy. Variable factors are included or removed as the situation requires. Production becomes driven far more by demand than in the past. The firm can respond to change and market volatility with greater agility.

2. Collaborative ventures and solutions expand

Collaboration strengthens relationships critical for maintaining high levels of customer satisfaction and retention. These new collaborations can occur within a firm, with customers, and even among competing companies.

Internal systems and analytics will benefit greatly from shared data. Take asset management as an example. Real-time financial data, including customer demand, production and exploration costs, and commodity pricing, can be correlated. Investment decisions, bullish or bearish, can be managed in a far more comprehensible way. Both short- and long-term risks are mitigated. Profitability grows.

Data analysis allows mining companies to buy and sell projects to maximize revenue while maintaining a focus on strategic priorities and core competencies.

Digitized information opens up brand-new service opportunities. Today, individual customer needs can be addressed. Customer-specific solutions, whether in transportation, tracking, inventory control, or safety monitoring are possible. These new services can be sold as separate packages or bundled with product sales. The gathered and analyzed information becomes a new revenue stream for mining firms.

Collaboration with other mining companies is also easier. For example, customers wanting blended grades of product can be served by shared information among competitors. Firms that could not deliver desired blends on their own can still gain market share.

3. Boldly going to new frontiers

The increased use of robots and automation open up new pockets of opportunity. Mining companies can access submerged material. Underwater mining and Arctic exploration are viable and profitable options.

Those pockets of opportunity will be become clearer in traditional mining spaces, too. Answering the question “What’s in the ground?” is getting easier. Automation and analytics are making what had been disjointed processes seamless.

Decisions in resource intelligence improve with collaborative data. The days are numbered for the old ways. Information and processes do not need to be scattered across company departments. Data source and geological model variances can be collected, corrected, and stored quickly.

Miners will have much better insights throughout the production cycle. Ore-body model data, blast-hole drill data, and online sampling are combined in new platforms. Statistical programs allow for better predictive modeling.

The cost reductions and profit opportunities are considerable. Discovery probability leaps higher. Drilling targets are more precise. A central repository for geological information leads to optimal blast and drill patterns. Mine plans are more accurate. Mining operations have less downtime and produce more expected product.

These improvements allow for less or no reliance on older methods such as manual plant assays, core logging, and face inspections.

Preparing to change

New business models require new ways of approaching the work. Companies wanting to reach digital maturity should consider the following actions.

First, be open to experimentation. Work within your organization to identify insights. Share them with stakeholders. Find examples of approaches to digital innovation that worked within mining or in other industries.

Second, prepare for change. A culture of change must be in place for data-driven processes, robotics, and automation to succeed. Leaders need to be willing to change and rethink long-held beliefs and assumptions.

Finally, be bold. Granted, most mining firms have significant sunk legacy capital and data costs. There will need to be an acceptance that innovation requires measured, informed, and acceptable investment and risk.

Join a LiveTwitterChat on Digitization in Mining on May 4th from 10:00-11:00am EST.  Use #digitalmining

The global Mining and Metals industry is going to come together to talk more about digital innovation impacting the mining industry July 12-14 at the International SAP Conference for Mining and Metals in Frankfurt, Germany.  Click to find out more and register. Don’t miss this opportunity to meet with world leaders and learn how your organization can become a connected, digital enterprise.

AA Mining and Metals Forum

Follow who is coming and speaking and pre-event activities by following sapmmconf and @sapmillmining on Twitter

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Ruediger Schroedter

About Ruediger Schroedter

Ruediger Schroedter is responsible for solution management of SAP solutions for the mining industry worldwide. He has spent more than 15 years in the mill products and mining industries and has extensive experience implementing SAP solutions for customers in these industries before coming to SAP.

Data Analysts And Scientists More Important Than Ever For The Enterprise

Daniel Newman

The business world is now firmly in the age of data. Not that data wasn’t relevant before; it was just nowhere close to the speed and volume that’s available to us today. Businesses are buckling under the deluge of petabytes, exabytes, and zettabytes. Within these bytes lie valuable information on customer behavior, key business insights, and revenue generation. However, all that data is practically useless for businesses without the ability to identify the right data. Plus, if they don’t have the talent and resources to capture the right data, organize it, dissect it, draw actionable insights from it and, finally, deliver those insights in a meaningful way, their data initiatives will fail.

Rise of the CDO

Companies of all sizes can easily find themselves drowning in data generated from websites, landing pages, social streams, emails, text messages, and many other sources. Additionally, there is data in their own repositories. With so much data at their disposal, companies are under mounting pressure to utilize it to generate insights. These insights are critical because they can (and should) drive the overall business strategy and help companies make better business decisions. To leverage the power of data analytics, businesses need more “top-management muscle” specialized in the field of data science. This specialized field has lead to the creation of roles like Chief Data Officer (CDO).

In addition, with more companies undertaking digital transformations, there’s greater impetus for the C-suite to make data-driven decisions. The CDO helps make data-driven decisions and also develops a digital business strategy around those decisions. As data grows at an unstoppable rate, becoming an inseparable part of key business functions, we will see the CDO act as a bridge between other C-suite execs.

Data skills an emerging business necessity

So far, only large enterprises with bigger data mining and management needs maintain in-house solutions. These in-house teams and technologies handle the growing sets of diverse and dispersed data. Others work with third-party service providers to develop and execute their big data strategies.

As the amount of data grows, the need to mine it for insights becomes a key business requirement. For both large and small businesses, data-centric roles will experience endless upward mobility. These roles include data anlysts and scientists. There is going to be a huge opportunity for critical thinkers to turn their analytical skills into rapidly growing roles in the field of data science. In fact, data skills are now a prized qualification for titles like IT project managers and computer systems analysts.

Forbes cited the McKinsey Global Institute’s prediction that by 2018 there could be a massive shortage of data-skilled professionals. This indicates a disruption at the demand-supply level with the needs for data skills at an all-time high. With an increasing number of companies adopting big data strategies, salaries for data jobs are going through the roof. This is turning the position into a highly coveted one.

According to Harvard Professor Gary King, “There is a big data revolution. The big data revolution is that now we can do something with the data.” The big problem is that most enterprises don’t know what to do with data. Data professionals are helping businesses figure that out. So if you’re casting about for where to apply your skills and want to take advantage of one of the best career paths in the job market today, focus on data science.

I’m compensated by University of Phoenix for this blog. As always, all thoughts and opinions are my own.

For more insight on our increasingly connected future, see The $19 Trillion Question: Are You Undervaluing The Internet Of Things?

The post Data Analysts and Scientists More Important Than Ever For the Enterprise appeared first on Millennial CEO.

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Daniel Newman

About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies. Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book "The Millennial CEO." Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter. Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5). A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

When Good Is Good Enough: Guiding Business Users On BI Practices

Ina Felsheim

Image_part2-300x200In Part One of this blog series, I talked about changing your IT culture to better support self-service BI and data discovery. Absolutely essential. However, your work is not done!

Self-service BI and data discovery will drive the number of users using the BI solutions to rapidly expand. Yet all of these more casual users will not be well versed in BI and visualization best practices.

When your user base rapidly expands to more casual users, you need to help educate them on what is important. For example, one IT manager told me that his casual BI users were making visualizations with very difficult-to-read charts and customizing color palettes to incredible degrees.

I had a similar experience when I was a technical writer. One of our lead writers was so concerned with readability of every sentence that he was going through the 300+ page manuals (yes, they were printed then) and manually adjusting all of the line breaks and page breaks. (!) Yes, readability was incrementally improved. But now any number of changes–technical capabilities, edits, inserting larger graphics—required re-adjusting all of those manual “optimizations.” The time it took just to do the additional optimization was incredible, much less the maintenance of these optimizations! Meanwhile, the technical writing team was falling behind on new deliverables.

The same scenario applies to your new casual BI users. This new group needs guidance to help them focus on the highest value practices:

  • Customization of color and appearance of visualizations: When is this customization necessary for a management deliverable, versus indulging an OCD tendency? I too have to stop myself from obsessing about the font, line spacing, and that a certain blue is just a bit different than another shade of blue. Yes, these options do matter. But help these casual users determine when that time is well spent.
  • Proper visualizations: When is a spinning 3D pie chart necessary to grab someone’s attention? BI professionals would firmly say “NEVER!” But these casual users do not have a lot of depth on BI best practices. Give them a few simple guidelines as to when “flash” needs to subsume understanding. Consider offering a monthly one-hour Lunch and Learn that shows them how to create impactful, polished visuals. Understanding if their visualizations are going to be viewed casually on the way to a meeting, or dissected at a laptop, also helps determine how much time to spend optimizing a visualization. No, you can’t just mandate that they all read Tufte.
  • Predictive: Provide advanced analytics capabilities like forecasting and regression directly in their casual BI tools. Using these capabilities will really help them wow their audience with substance instead of flash.
  • Feature requests: Make sure you understand the motivation and business value behind some of the casual users’ requests. These casual users are less likely to understand the implications of supporting specific requests across an enterprise, so make sure you are collaborating on use cases and priorities for substantive requests.

By working with your casual BI users on the above points, you will be able to collectively understand when the absolute exact request is critical (and supports good visualization practices), and when it is an “optimization” that may impact productivity. In many cases, “good” is good enough for the fast turnaround of data discovery.

Next week, I’ll wrap this series up with hints on getting your casual users to embrace the “we” not “me” mentality.

Read Part One of this series: Changing The IT Culture For Self-Service BI Success.

Follow me on Twitter: @InaSAP

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How Much Will Digital Cannibalization Eat into Your Business?

Fawn Fitter

Former Cisco CEO John Chambers predicts that 40% of companies will crumble when they fail to complete a successful digital transformation.

These legacy companies may be trying to keep up with insurgent companies that are introducing disruptive technologies, but they’re being held back by the ease of doing business the way they always have – or by how vehemently their customers object to change.

Most organizations today know that they have to embrace innovation. The question is whether they can put a digital business model in place without damaging their existing business so badly that they don’t survive the transition. We gathered a panel of experts to discuss the fine line between disruption and destruction.

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qa_qIn 2011, when Netflix hiked prices and tried to split its streaming and DVD-bymail services, it lost 3.25% of its customer base and 75% of its market capitalization.²︐³ What can we learn from that?

Scott Anthony: That debacle shows that sometimes you can get ahead of your customers. The key is to manage things at the pace of the market, not at your internal speed. You need to know what your customers are looking for and what they’re willing to tolerate. Sometimes companies forget what their customers want and care about, and they try to push things on them before they’re ready.

R. “Ray” Wang: You need to be able to split your traditional business and your growth business so that you can focus on big shifts instead of moving the needle 2%. Netflix was responding to its customers – by deciding not to define its brand too narrowly.

qa_qDoes disruption always involve cannibalizing your own business?

Wang: You can’t design new experiences in existing systems. But you have to make sure you manage the revenue stream on the way down in the old business model while managing the growth of the new one.

Merijn Helle: Traditional brick-and-mortar stores are putting a lot of capital into digital initiatives that aren’t paying enough back yet in the form of online sales, and they’re cannibalizing their profits so they can deliver a single authentic experience. Customers don’t see channels, they see brands; and they want to interact with brands seamlessly in real time, regardless of channel or format.

Lars Bastian: In manufacturing, new technologies aren’t about disrupting your business model as much as they are about expanding it. Think about predictive maintenance, the ability to warn customers when the product they’ve purchased will need service. You’re not going to lose customers by introducing new processes. You have to add these digitized services to remain competitive.

qa_qIs cannibalizing your own business better or worse than losing market share to a more innovative competitor?

Michael Liebhold: You have to create that digital business and mandate it to grow. If you cannibalize the existing business, that’s just the price you have to pay.

Wang: Companies that cannibalize their own businesses are the ones that survive. If you don’t do it, someone else will. What we’re really talking about is “Why do you exist? Why does anyone want to buy from you?”

Anthony: I’m not sure that’s the right question. The fundamental question is what you’re using disruption to do. How do you use it to strengthen what you’re doing today, and what new things does it enable? I think you can get so consumed with all the changes that reconfigure what you’re doing today that you do only that. And if you do only that, your business becomes smaller, less significant, and less interesting.

qa_qSo how should companies think about smart disruption?

Anthony: Leaders have to reconfigure today and imagine tomorrow at the same time. It’s not either/or. Every disruptive threat has an equal, if not greater, opportunity. When disruption strikes, it’s a mistake only to feel the threat to your legacy business. It’s an opportunity to expand into a different marke.

SAP_Disruption_QA_images2400x1600_4Liebhold: It starts at the top. You can’t ask a CEO for an eight-figure budget to upgrade a cloud analytics system if the C-suite doesn’t understand the power of integrating data from across all the legacy systems. So the first task is to educate the senior team so it can approve the budgets.

Scott Underwood: Some of the most interesting questions are internal organizational questions, keeping people from feeling that their livelihoods are in danger or introducing ways to keep them engaged.

Leon Segal: Absolutely. If you want to enter a new market or introduce a new product, there’s a whole chain of stakeholders – including your own employees and the distribution chain. Their experiences are also new. Once you start looking for things that affect their experience, you can’t help doing it. You walk around the office and say, “That doesn’t look right, they don’t look happy. Maybe we should change that around.”

Fawn Fitter is a freelance writer specializing in business and technology. 

To learn more about how to disrupt your business without destroying it, read the in-depth report Digital Disruption: When to Cook the Golden Goose.

Download the PDF (1.2MB)

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Digitization Of The Supplier Network: Grinding Away Competitive Edges

Kai Goerlich

Competitors with advanced digital capabilities are invading markets with new disruptive business models – and a range of new challenges across all industries. Prices are falling and changing quickly. Margins are thinning. Resources are increasingly volatile while the balance between supply and fast-changing customer demands are next-to-impossible to match. All the while, 30% of industry leaders are at risk of being disrupted by 2018 by a digitally enabled competitor, according to IDC.

Under these conditions, companies are beginning to ask whether their supply networks should be open to the digital world. Will they accept the risk of being copied and losing competitive advantage? Or will they secure their best practices in supply chain and logistics?

Using an analytical framework of 15 ecosystem factors, we compared traditional companies against digital newcomers. Our ad hoc study revealed that digitization influences business systems on several levels, but standard best practices are not one of them.

Network resiliency

In most supply chains, the hierarchical model is still living and prospering. Digital newcomers usually create a web-like structure across the entire business. While the traditional approach may guarantee price stability and quality, this web structure allows a much faster ramp-up and exchange of partners – making it more resilient to change.

Dependencies

In traditional networks, the business is likely evolving around mutual advantages. Very often, there are tight, symbiotic business connections with limited sets of partners. New digital networks are operating with an increased focus on leveraging opportunities. Plus, partners are encouraged to participate, widen, and promote the network – even if they do not directly contribute to revenue or profit margins.

Brand management

Web structures are especially attractive to companies that find it difficult to access traditional value chains. In general, classic supply chains cannot keep up with the speed of change nor deal with new and unexpected supply-chain partners in future digital networks. And as “new and unexpected” translate into “interesting and exciting” for consumers, companies may encounter significant branding issues.

Path dependency

Digital newcomers usually have a lower path dependency, such as mode of action. Unfortunately, this can be attributed to perspectives and business plans that are not based on decades of experience in one business. Of course, knowing a business for many years has its advantages as well – but only if knowledge is successfully transferred into the digital world.

A new way to operate

As pointed out in an earlier blog, digitization is proven to be a shortcut for some traditional processes and functions. In turn, embedding best practices into supply-chain and logistics processes and avoiding any transfer of knowledge as long as possible may appear to be an obvious solution. However, according to our findings, it might not be the best path to dealing with changes related to digital transformation.

While digitization may indeed wash away former competitive advantages, it also empowers companies to use their vast knowledge and connections to get on par with digital newcomers – on a new and different level. For example, most traditional best practices are now outsourced and can be easily applied as a service. But more important, instead of waiting to be disrupted by digitization, businesses can become as flexible as possible to enhance the customer experience and build loyalty.

For more on disruption without damage, see 4 Ways to Digitally Disrupt Your Business Without Destroying It.

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Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Idea Director of Thought Leadership at SAP. His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation.