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How A Data-Driven Culture Enables Innovation And Empowerment In An Adaptive Enterprise

Mala Anand

Data is the fuel for the digital economy and is at the core of driving insight-driven business transactions – from decision-making to cross-departmental collaboration. Organizations deal with an abundance of data across the enterprise, creating an opportunity to deliver insights and drive material outcomes to gain a competitive advantage.

For example, automobile companies rely on consumer, competitive, financial, and market data to determine which new features and technology to add to next-generation cars. In the hospitality industry, marketing teams model consumer-behavior data to personalize offers for guests. Farmers leverage data to determine the best times for planting crops and fertilizing and irrigating their land. Even healthcare organizations rely on data to define standardized materials and surgical instruments for the operating room.

In each of these scenarios, insights from data are driving increased sales, reducing operational expenses, generating higher crop yields, and improving customer service or patient care. Collectively, these insights are driving outcomes with real, actionable impact on businesses and people’s lives.

Reaching this inflection point starts with companies committing to redefining their businesses and creating data-driven cultures. That culture can take hold when companies establish three goals: break down data silos, empower teams to explore data, and engage teams through leadership.

1. Data must be socialized

To break down data silos, companies are transitioning from isolated data platforms, designed to support a business unit or role, to centralized platforms with multi-team access. This technology shift synergizes with today’s cross-department, design-thinking collaboration strategies. Instead of groups maintaining their own work styles and being dedicated to discreet projects, companies are forming diverse teams made up of individuals from different groups and backgrounds that share expertise and knowledge.

This type of culture strives to make the knowledge held by data and people hyper-collaborative and communicated across the company. Customer purchase histories, addresses, and demographics, for example, aren’t available only for sales and marketing. Other business groups and project teams can access this valuable CRM data for their purposes, and they can manipulate and test business and operations data.

2. Data-driven cultures work together to empower teams

By breaking data free from silos, employees working in marketing, finance, supply chain, and every other group have first-hand knowledge of the business processes in their groups. Their in-the-trenches experiences make them the best source for engaging with the data and pushing it toward creating better business outcomes. These teams, working under a comprehensive data governance plan, need centralized analytics tools that let them interact with the data. A platform that enables assigned levels of access and role-based security keeps data-driven cultures within the defined governance outlined by IT departments. Most importantly, this modern-day approach is infinitely faster than previous models, where a data query was sent to IT and a report would appear weeks later. A data-driven culture lets a non-expert query and manipulate the data and visualize the results immediately.

3. Executive support separates data-driven cultures from traditional businesses

In a data-driven culture, managers encourage employees to interact with data and take action. Teams have the freedom to quickly take action, review, and respond to the results. It’s understood that not all results will be positive, and learning comes from both good and bad results. What’s important is feeding data into models and supporting an iterative process so that business decisions and outcomes become more precise each time.

In tandem with this support, data-driven leaders rely on dashboards in their day-to-day activities and they share the data behind the company’s business decisions and the results. This leads to transparency around changes and shifts in the businesses. When the leaders showcase data as a hero, others in the organization will follow suit and begin immersing themselves in putting data to work.

Realizing an adaptive enterprise

Once these changes are underway, the possibilities are endless. Companies can break into new markets, pursue a desired demographic, or create business models built around untapped assets. Data will manifest in unexpected ways, as businesses become more empathetic and aware of their customers’ needs. Under Armour, for example, created apps tied to Fitbit for its customers committed to exercise. Once a company can put itself in its customers’ shoes, it can create service models and products that cut costs, create efficiencies, and improve customer engagement.

That insight to empathy is only possible in an adaptive enterprise, which is derived from a data-driven culture. Adaptive enterprises respond to customers, partners, and market changes in real time based on insights from data. To stay ahead, they constantly ask: What did we do today? Where have we been? Where are we going?

Adaptive enterprises answer those questions through a mixture of reports, or bimodal IT (as Gartner refers to it). One set is the familiar, core business reports that business analysts email out every Friday, for example. Adaptive enterprises add in a second set of reports that is more experimental and agile. They look at marketplace activities, including tests, trials, and theories that are shaking up the industry and causing disruptions. Adaptive enterprises integrate these two modes to gain a common view across the business. From this central platform, teams throughout the company can test and hypothesize, productize, and operationalize by manipulating the data. They cycle through multiple tests and iterations, always pouring the learnings back into the business.

Data scrubs in at Mercy

Mercy, a longtime pioneer and advocate for quality healthcare, has traveled this journey from traditional healthcare organization to a data-driven culture and won awards on the way. The St. Louis-based healthcare organization recently won the HIMSS Nicholas E. Davies Award of Excellence, which recognizes healthcare organizations that use health IT to improve patient care while reducing costs, and it is a first place winner of the 2016 SAP HANA Innovation Award.

Millions of patients visit Mercy’s 43 acute care and specialty hospitals hoping to find pain relief and feel better. Most of these patients are unaware that their caregivers at Mercy are not only trained in the latest healthcare procedures, they are also taking advantage of the organization’s data to drive better outcomes.

Data sets from electronic medical records, financing, and business processes are available for every group to run tests against, giving Mercy greater visibility into variations of clinical care for patients experiencing heart failure, pneumonia, or surgery. Opening up the data and empowering its employees to iterate has led to $9.2M saved by eliminating or minimizing the use of certain surgical products, reducing variation in surgical protocols, and establishing best practices across surgical departments to ensure quality in postoperative results for patients.

What is happening at Mercy and other data-driven organizations can be replicated. Of course every organization will have unique challenges, but each can leverage this blueprint of breaking down silos, empowering the team, leading by example, recognizing possibilities, creating an adaptive enterprise, and iterating, iterating, iterating.

The future is data, and it is driving business outcomes from the boardroom to the operating room – and everywhere in between.

Learn more about mining Data – The Hidden Treasure Inside Your Business.

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Mala Anand

About Mala Anand

Mala Anand is the President of Analytics at SAP, leading the end-to-end business including go-to-market, product development and strategy. With her primary focus on product development, market acceleration and adoption in one of SAP’s core innovation areas, Mala develops and executes strategy across all markets and ensures operational excellence within the global GTM and product development teams. The core focus of the SAP Analytics business encompasses business intelligence with embedded predictive and machine learning innovations across large data sets. Formerly, Mala led the Data & Analytics | Automation Software Platforms business at Cisco Systems with a focus on innovative solutions to aggregate and analyze today’s hyper-distributed and real-time streaming data. With over 20 years of experience as a senior software executive, Mala places a deep focus on delivering innovative solutions to the market that help customers develop informed, timely insights to establish new modes of engaging their workforce and customers.

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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The Future of Cybersecurity: Trust as Competitive Advantage

Justin Somaini and Dan Wellers

 

The cost of data breaches will reach US$2.1 trillion globally by 2019—nearly four times the cost in 2015.

Cyberattacks could cost up to $90 trillion in net global economic benefits by 2030 if cybersecurity doesn’t keep pace with growing threat levels.

Cyber insurance premiums could increase tenfold to $20 billion annually by 2025.

Cyberattacks are one of the top 10 global risks of highest concern for the next decade.


Companies are collaborating with a wider network of partners, embracing distributed systems, and meeting new demands for 24/7 operations.

But the bad guys are sharing intelligence, harnessing emerging technologies, and working round the clock as well—and companies are giving them plenty of weaknesses to exploit.

  • 33% of companies today are prepared to prevent a worst-case attack.
  • 25% treat cyber risk as a significant corporate risk.
  • 80% fail to assess their customers and suppliers for cyber risk.

The ROI of Zero Trust

Perimeter security will not be enough. As interconnectivity increases so will the adoption of zero-trust networks, which place controls around data assets and increases visibility into how they are used across the digital ecosystem.


A Layered Approach

Companies that embrace trust as a competitive advantage will build robust security on three core tenets:

  • Prevention: Evolving defensive strategies from security policies and educational approaches to access controls
  • Detection: Deploying effective systems for the timely detection and notification of intrusions
  • Reaction: Implementing incident response plans similar to those for other disaster recovery scenarios

They’ll build security into their digital ecosystems at three levels:

  1. Secure products. Security in all applications to protect data and transactions
  2. Secure operations. Hardened systems, patch management, security monitoring, end-to-end incident handling, and a comprehensive cloud-operations security framework
  3. Secure companies. A security-aware workforce, end-to-end physical security, and a thorough business continuity framework

Against Digital Armageddon

Experts warn that the worst-case scenario is a state of perpetual cybercrime and cyber warfare, vulnerable critical infrastructure, and trillions of dollars in losses. A collaborative approach will be critical to combatting this persistent global threat with implications not just for corporate and personal data but also strategy, supply chains, products, and physical operations.


Download the executive brief The Future of Cybersecurity: Trust as Competitive Advantage.


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To Get Past Blockchain Hype, We Must Think Differently

Susan Galer

Blockchain hype is reaching fever pitch, making it the perfect time to separate market noise from valid signals. As part of my ongoing conversations about blockchain, I reached out to several experts to find out where companies should consider going from here. Raimund Gross, Solution Architect and Futurist at SAP, acknowledged the challenges of understanding and applying such a complex leading-edge technology as blockchain.

“The people who really get it today are those able to put the hype in perspective with what’s realistically doable in the near future, and what’s unlikely to become a reality any time soon, if ever,” Gross said. “You need to commit the resources and find the right partners to lay the groundwork for success.”

Gross told me one of the biggest problems with blockchain – besides the unproven technology itself – was the mindset shift it demands. “Many people aren’t thinking about decentralized architectures with peer-to-peer networks and mash-ups, which is what blockchain is all about. People struggle because often discussions end up with a centralized approach based on past constructs. It will take training and experience to think decentrally.”

Here are several more perspectives on blockchain beyond the screaming headlines.

How blockchain disrupts insurance, banking

Blockchain has the potential to dramatically disrupt industries because the distributed ledger embeds automatic trust across processes. This changes the role of longstanding intermediaries like insurance companies and banks, essentially restructuring business models for entire industries.

“With the distributed ledger, all of the trusted intelligence related to insuring the risk resides in the cloud, providing everyone with access to the same information,” said Nadine Hoffmann, global solution manager for Innovation at SAP Financial Services. “Payment is automatically triggered when the agreed-upon risk scenario occurs. There are limitations given regulations, but blockchain can open up new services opportunities for established insurers, fintech startups, and even consumer-to-consumer offerings.”

Banks face a similar digitalized transformation. Long built on layers of steps to mitigate risk, blockchain offers the banking industry a network of built-in trust to improve efficiencies along with the customer experience in areas such as cross-border payments, trade settlements for assets, and other contractual and payment processes. What used to take days or even months could be completed in hours.

Finance departments evolve

Another group keenly watching blockchain developments are CFOs. Just as Uber and Airbnb have disrupted transportation and hospitality, blockchain has the potential to change not only the finance department — everything from audits and customs documentation to letters of credit and trade finance – but also the entire company.

“The distributed ledger’s capabilities can automate processes in shared service centers, allowing accountants and other employees in finance to speed up record keeping including proof of payment supporting investigations,” said Georg Koester, senior developer, LoB Finance at the Innovation Center Potsdam. “This lowers costs for the company and improves the customer experience.”

Koester said that embedding blockchain capabilities in software company-wide will also have a tremendous impact on product development, lean supply chain management, and other critical areas of the company.

While financial services dominate blockchain conversations right now, Gross named utilities, healthcare, public sector, real estate, and pretty much any industry as prime candidates for blockchain disruption. “Blockchain is specific to certain business scenarios in any industry,” said Gross. “Every organization can benefit from trust and transparency that mitigates risk and optimizes processes.”

Get started today! Run Live with SAP for Banking. Blast past the hype by attending the SAP Next-Gen Boot Camp on Blockchain in Financial Services and Public Sector event being held April 26-27 in Regensdorf, Switzerland.

Follow me on Twitter, SCN Business Trends, or Facebook. Read all of my Forbes articles here.

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