6 items tagged "CIO"

  • Business Intelligence and beyond: predictions for 2016

    businessIt’s been an interesting year for BI – and 2016 looks set to be no different

    Here are some predictions on what we believe next year has in store, in particular for the data and analytics industry.

    1. Cannibalisation of the channel
    Next year will see many vendors looking to take back control, rather than invest in their channel partners. The danger for the channel is that this will result in vendors keeping good deals or redirecting services projects back to themselves. Platforms such as Amazon Web Services and Microsoft Azure have grown exponentially this year. Another risk is the continued trend of vendors developing hosted solutions, via platforms such as these that cut out their channel partners. In response to this, the channel needs to look for vendors with a transparent indirect strategy in place and form mutually beneficially relationships.

  • Data, Analytics & Fuel Innovation at Celgene

    Williams-Richard-CelgeneCIO Richard Williams leads a global IT organization that’s harnessing digital, data, and analytics to support R&D innovation, drive operational excellence, and help Celgene achieve first-mover advantage in the shift to value-based, personalized health care intended to help patients live longer and healthier lives.
     
     
    An explosion of electronic health information is rocking the entire health care ecosystem, threatening to transform or disrupt every aspect of the industry. In the biopharmaceutical sector, that includes everything from the way breakthrough scientific innovations and insights occur to clinical development, regulatory approvals, and reimbursement for innovations. Celgene, the $11 billion integrated global biopharmaceutical company, is no exception.
     
    Indeed, Celgene, whose mission is to discover, develop, and commercialize innovative therapies for the treatment of cancer, immune-inflammatory, and other diseases, is aggressively working to leverage the information being generated across the health care system, applying advanced analytics to derive insights that power its core business and the functions that surround and support it. Long known for its commitment to external scientific collaboration as a source of innovation, Celgene is investing to harness not only the data it generates across the enterprise, but also the real-world health care data generated by its expanding network of partners. Combined, this network of networks is powering tremendous value.
     
    CIO Richard Williams sees his mission—and that of the IT organization he leads—as providing the platforms, data management, and analytics capabilities to support Celgene through the broader industry transition to value-based, personalized health care. At Celgene, this transformation is enabled by a focus on the seamless integration of information and technology. A cloud-first platform strategy, coupled with enterprise information management, serves as the foundation for leveraging the data generated and the corresponding insights from internal and external health care data.
     
    Williams recently shared his perspective on the changes wrought by enormous data volumes in health care, the role of IT at Celgene, and the ways IT supports life sciences innovation.
     
    Can you describe the environment in which Celgene is currently operating?
     
    Williams: We are living in an exciting era of scientific breakthroughs coupled with technology convergence. This creates both disruption and opportunity. The explosion and availability of data, the cloud, analytics, mobility, artificial intelligence, cognitive computing, and other technologies are accelerating data collection and insight generation, opening new pathways for collaboration and innovation. At Celgene, we’re able to apply technology as never before—in protein homeostasis, epigenetics, immuno-oncology, immuno-inflammation, informatics, and other fields of study—to better understand disease and develop targeted therapies and treatments for people who desperately need them.
     
    How does IT support scientific and business innovation at Celgene?
     
    At its core, Celgene IT is business aligned and value focused. Rather than looking at technology for technology’s sake, we view information and technology as essential to achieving our mission and business objectives. As an integrated function, we have end-to-end visibility across the value chain. This enables us to identify opportunities to leverage technology investments to connect processes and platforms across all functions. As a result, we’re able to support improvements in R&D productivity, product launch effectiveness, and overall operational excellence.
     
    This joint emphasis on business alignment and business value, which informs everything we do, is manifest in three important ways:
     
    First is our emphasis on a core set of enterprise platforms, which enable us to provide end-to-end visibility rather than a narrower functional view. We established a dual information- and cloud-first strategy to provide more comprehensive platforms of capabilities that can be shared across Celgene’s businesses. The cloud—especially with recent advances in security and analytics—provides tremendous scale, agility, and value because it allows us to standardize and create both consistency and agility across the entire organization regardless of device or access method. It’s our first choice for applications, compute power, and storage.
     
    Second is our focus on digital and the proliferation of patient, consumer, scientific, and it is creating. Health care data is growing exponentially—from something like 500 petabytes (PB) of data in 2013 to 25,000 PB by 2020, according to one study.
     
    To address this opportunity, we’ve initiated an enterprise information management (EIM) strategy through which we are targeting important data domains across our business and applying definitions, standards, taxonomies, and governance to data we capture internally and from our external partners. Establishing that consistency is critically important. It drives not only innovation, but also insight into our science, operations, and, ultimately, patient outcomes. Celgene is at the forefront in leveraging technologies that offer on-demand compute and analytic services. By establishing data consistency and influencing and setting standards, we will support our own objectives while also benefiting the broader industry.
     
    Third is our support for collaboration—the network of networks—and the appropriate sharing of information across organizational boundaries. We want to harness the capabilities and data assets of our partners to generate insights that improve our science and our ability to get better therapies to patients faster. Celgene is well-known in the industry for external innovation—how we partner scientifically—and we are now extending this approach to data and technology collaboration. One recent example is our alliance with Medidata Solutions, whose Clinical Cloud will serve as our enterprise technology and data platform for Celgene clinical trials worldwide. Celgene is also a founding commercial member of the Oncology Research Information Exchange Network, a collaboration of cancer centers spearheaded by M2Gen, a health informatics solution company. And we have teamed with ConvergeHEALTH by Deloitte and several other organizations for advanced analytics around real-world evidence and knowledge management, which will also be integrated into our data platform.
     
    You’re building this network-enabled, data-rich environment. But are your users prepared to take advantage of it?
     
    That’s an important aspect of the transformation and disruption taking place across multiple industries. Sure, IT can make information, technology, and insights available for improved decision-making, but the growing complexity of the data—whether it’s molecular structures, genomics, electronic medical records, or payment information—demands different skill sets.
     
    Data scientists are in high demand. We need to embed individuals with those specialized skills in functions from R&D to supply chain and commercial. At the same time, many more roles will require analytics acumen as part of the basic job description.
     
    As you build out your platform and data strategies, are you likely to extend those to your external alliances and partners?
     
    External collaboration enabled by shared data and analytics platforms is absolutely part of our collaboration strategy. If our informatics platforms can help our academic or commercial biotech collaborators advance the pace of their scientific evaluations, clinical studies, and commercialization, or they can help us with ours, that’s a win-win situation—and a differentiator for Celgene. We are already collaborating with Sage Bionetworks, leveraging Apple ResearchKit to develop an app that engages patients directly in innovation aimed at improving treatments for their diseases. We’re also working with IBM Watson to increase patient safety using cognitive computing to improve drug monitoring. As the power of collaborative innovation continues, collaboration will become more commonplace and lead to some amazing results.
     
    As you look out 12 to 18 months, what technologies might you want to bolt onto this platform or embed in your EIM strategy?
     
    The importance of cognitive computing, including machine learning and artificial intelligence, will continue to grow, helping us to make sense of the increasing volumes of data. The continued convergence of these technologies with the internet of things and analytics is another area to watch. It will result in operational insights as well as new, more intelligent ways to improve treatments for disease.
     
    What advice do you have for CIOs in health care or other industries who may not be as far along in their cloud, data, and analytics journeys?
    A digital enterprise is a knowledge- and information-driven enterprise, so CIOs should first focus on providing technologies and platforms that support seamless information sharing. In the process, CIOs should constantly be looking at information flows through an enterprise lens—real value is created when information is connected across all functions. Next, it’s increasingly important for CIOs to help build a technology ecosystem that allows the seamless exchange of information internally and externally because transformation and insight will occur in both places. Last, CIOs need to recognize that every job description will include data and information skills. This is an especially exciting time to be in IT because the digital capabilities we provide increasingly affect every function and role. We need to help people develop the skills they need to take advantage ofwhat we can offer now and in the future.
    Source: deloitte.wsj.com, November 14, 2016
  • Digital Transformation Requires Total Organizational Commitment

    shutterstock 127574942By now you’ve surely heard that moving forward, every company will be a software company, and that shift is happening now as companies large and small scramble to transform into digitally-driven organizations.

    Wherever you turn, businesses are facing tremendous disruptive pressure. What’s interesting is that the theory about how firms should be dealing with this massive change is itself in flux, transforming if you will, as organizations come to grips with the idea that the most basic ways they do business are being called into question.

    Just over a year ago when I researched this topic, I found that the general method for dealing with disruption was developing pockets of innovation inside a company using labs or incubators to prime the innovation pump. Today, when I explore the same issues, I’m finding that companies are taking a much more comprehensive approach that has to do with reviewing every department and business process in the organization.

    The issue with the lab or incubator concept is how you move the kind of innovative thinking from that internal innovation test bed into the organization at large. The reasoning behind isolating innovation was sound enough, because those fledgling ideas would very likely be sucked up into the vacuum of existing business policies where they get lost forever in a haze of bureaucratic negativity. If you want to kill innovation, you just keep saying “no.”

    The new thinking says you have to start looking at the big picture from the first day and you have to consider the impact that these changes are going to have on the entire organization. You have to figure out how to grease the skids of creativity so they don’t get slowed down by HR, legal, IT and by all the systems and departments that have been put in place to protect and limit these kinds of changes inside large organizations. Now the idea is to teach those well-meaning naysayers to get the heck out of the way and for them to also find new ways of achieving their goals and requirements as the organization marches forward into a digitally driven future.

    Thinking Bigger Picture

    As we’ve seen through the experience of implementing individual enterprise systems such as content management, ERP or CRM trying to get a large organization moving in the same direction across departments is a huge challenge. When you suddenly put your whole business model on notice, a pocket of innovation is just too incremental to deal with that scale of change.

    Aaron Levie, CEO at Box is co-teaching a course this semester at Stanford with professor Rob Siegel called The Industrialist’s Dilemma where they explore the kinds of issues large established organizations face as they maneuver through these massive changes.

    “What happens when you take a business that’s good at analog stores, and software can deliver new disruptive experiences? How do they respond? No product is more physical and analog than a retail store or car. We are seeing those [delivery models] inverted and flipped over by technology,” says Levie.

    When I spoke to Edward Hiaett, SVP of services at Pivotal and in charge of Pivotal Labs, at Web Summit in October, 2014, his company was one of those organizations working on the pockets of innovation approach, but he said his company’s thinking has evolved.

    When he looks at a firm like one of his clients, Ford, he sees a company that has to completely change the way it does business. In the next decade it’s possible that many people won’t own cars in the traditional sense. In fact they might not even be driving them anymore as self-driven cars become more widespread. That means the whole firm has to start examining all of its long-established systems around how they design, deliver, market and sell automobiles.

    And they need to start looking at these systems now before the delivery model changes, Hiaett says. It doesn’t mean it changes all at once, but if Ford is in the midst of pivoting from a business selling cars to one that’s in the ‘the mobility business’, it’s clearly going to have a major impact on all of the company’s long-established business processes.

    Clarity Of Vision

    This means that the executive suite has to have a clear plan for the future, and a way to put the company on the road toward delivering on that vision. They can’t hide the innovation team in the basement. They need to inject innovative thinking into every process in the organization and that requires reconsidering every process, says Michael Krigsman, founder of cxotalk.com, a weekly web-based talk show on which Krigsman interviews leading tech industry executives.

    “The successful executives are able to embrace change. This is a very key point and it’s really the most difficult thing about this. With the exception of startups, every company has an established business model and way they do business. Product lines, services and employees have been optimized for standard processes,” Krigsman told TechCrunch.

    Executives require a particular set of skills and approaches as the organization shifts:

    digital-cio-mindset

    Levie says that he sees CIOs with these kinds of traits in his job as Box CEO, but he says he has seen organizations held back when there isn’t a unified front in the C suite.

    “I think the majority of companies recognize how disruptive these trends are. A small percentage recognize this at the CEO level and board level. Me personally in building and selling enterprise software, we interact with a large percentage of CIOs that get it, but don’t always have the support from CEO and that makes it harder without top-down support,” Levie explained.

    It’s A People Problem

    As we tend to do in this business, we have been attacking this type of change by throwing different technologies at it, and while technology can certainly help, it requires a much more personal approach by management, one that takes the people who have to implement these massive changes into account.

    Just last week Accenture released its annual 2016 Technology Vision Report and the consulting juggernaut says the success of any company going through fundamental digital transformation is understanding that it’s first and foremost a people issue.

    Finding ways to help people across this digital divide and the culture shock that rapid change brings is going to be just as important as the technology we use to get there, says Marc Carrel-Billiard, global tech R&D Lead on digital transformation at Accenture.

    “When we talk to clients, we usually start by talking about technology, but [typically] after 15 minutes, we shift gears. We start talking about people and the digital culture shock they are in. If [clients] want to be digital, it’s not just about technological change because it’s coming [regardless]. Companies need to think about people or it will not work at all,” he said.

    How To Get There

    One lesson we should have learned after all these years of trying to implement incremental change management is that it’s always been about people and managing how to deal with these changes. Today, the speed of change is coming so quickly, and the requirements are so daunting, that it’s easy to get overwhelmed. It requires companies to shift their mindset completely, Krigsman says.

    “Companies that do this well are able to adopt a beginner’s mind set, taking an approach of looking at things from a fresh perspective,” he explained.

    This could involve, for example, having fewer impediments for customer service by implementing systems so that information flows more seamlessly from one department to another and across systems.

    “What does that mean to customers and internal processes? It comes down to being willing to experiment and look at things through a new lens,” Krigsman said.

    In fact, he recommends that companies partner with startups, which tend to be smaller, more nimble and creative. “The reason for that, the big challenge is how do you inject new thinking. And that’s a very hard thing to do because it comes down to several things, the ingrained behaviors of people who have been doing this job this way for a long time,” he said.

    By injecting new thinking into a company, employees can start to see that there are different ways to handle those standard business practices and can begin to incorporate that type of creative thinking into their organizational philosophy.

    When you consider that 88 percent of the Fortune 500 companies in 1955 are now gone, it’s not hard to see that change has always been with us, but the rate of change is accelerating dramatically due in large part to the disruption brought about by digital transformation.

    “The cool thing is that incumbents recognize that the same assets that can hold them back, can also be used to compete in a different guise,” Levie said. That means it’s not all gloom and doom, companies just have to start thinking much more creatively about their digital future and the effect that will have across the organization.

    Source: TechCrunch

  • Hoe groot is ‘the next big thing’?

    iotWat als IoT gewoon een overkoepelende term zou zijn voor manieren om iets bruikbaars te maken uit machine-gegenereerde data? Bijvoorbeeld, een bus vertelt mijn telefoon hoe ver mijn bushalte is en mijn fietsverhuur vertelt me ​​hoeveel fietsen beschikbaar zijn?

    In 2014 vroeg IDC 400 C-suite professionals wat volgens hen IoT was. De antwoorden varieerden van soorten apparaten (thermostaten, auto's, home security-systemen) tot uitdagingen (beveiliging, data management, connectiviteit). Dezelfde analist benadrukt ook dat de wereldwijde markt voor IoT oplossingen zal groeien van 1,9 biljoen in 2013 tot 7,1 biljoen dollar in 2020. Dit optimisme wordt ondersteund door Gartner’s inschatting: 4,9 miljard gekoppelde 'dingen' zullen in 2016 in gebruik zijn. In 2020 zullen dat er 25 miljard zijn.
    Met andere woorden: IoT is zeer divers en het potentieel is enorm. De waarde ligt niet alleen in de kosten van de sensoren. Het is veel meer dan dat.

    Wanneer IoT begint te vertellen
    Het IoT is niet iets dat op zichzelf staat. Het rijpt naast big data. Het uitrusten van miljarden objecten met sensoren is van beperkte waarde als het niet mogelijk is miljarden datastromen te genereren, verzenden, opslaan en te analyseren.
    De datawetenschapper is de menselijke choreograaf van dit IoT. Zij zijn essentieel voor het identificeren van de waarde van de enorme hoeveelheid data die al deze apparaten genereren. En dat is de reden waarom connectiviteit en opslag zo belangrijk zijn. Kleine geïsoleerde apparaten zonder opslag en weinig rekenkracht vertellen ons weinig. Alleen door naar grote verzamelingen data te kijken kunnen we correlaties ontdekken en wordt het mogelijk trends te herkennen en voorspellingen te doen.
    In elke zakelijke omgeving, is het scenario identiek: de CxO zal de informatie die er vandaag is bekijken ten opzichte van informatie die er was in het verleden om een voorspelbaar inzicht te krijgen in wat er gaat gebeuren in de toekomst.

    Sneller inzicht leidt tot concurrentievoordeel
    CxO’s willen tegenwoordig een ander soort bedrijf. Ze willen dat het in een snel tempo opereert en reageert op de markt, maar ze willen ook beslissingen nemen op basis van intelligentie verzameld via big data. En ze willen de beste producten maken, gebaseerd op klantinzicht. Bedrijven zijn op zoek naar een disruptief business model waardoor ze steeds meer in kunnen spelen op trends in de markt en daarmee een voorsprong hebben op de concurrentie.

    Start-up gedrag
    Het antwoord ligt in de volgende vraag aan bedrijven: "Waarom kunnen ondernemingen zich niet meer als start-ups gedragen?" Dit gaat niet over het maken van overhaaste beslissingen met weinig of geen overzicht. Het gaat over het aannemen van een slank business model dat onzekerheid en uitgerekte budgetten tolereert. En nog belangrijker, het gaat over hoe het management van het bedrijf een cultuur van slagvaardigheid neerzet.
    De organisaties die zullen winnen in het big data spel zijn niet degenen die de meeste of de beste toegang ertoe hebben. De winnaars omschrijven duidelijk hun doelen, zetten de nodige operationele grenzen en stellen vast wat de uitrusting is die nodig is om de klus te klaren.

    Leidende rol CIO's
    CxO’s hebben de zakelijke waarde van IT erkend, en willen dat CIO's meer een leidende rol nemen en in kaart brengen wat de toekomst is van het bedrijf. IT kan een enorme rol spelen in de bouw van die toekomst door samen te werken met de business en de tools te verschaffen die nodig zijn om productief te zijn. Technologie kan voortdurende innovatie op elk niveau vergemakkelijken, waardoor het bedrijf niet alleen kan overleven maar floreren.
    Het is niet niks om deze wens van bedrijven te bereiken. Maar samenwerken met technologie maakt het veel haalbaarder omdat het bedrijven in staat stelt tot een wendbare, innovatieve, data-gedreven toekomst te komen.

    Source: ManagersOnline

  • Information Is Now The Core Of Your Business

    DataData is at the very core of the business models of the future – and this means wrenching change for some organizations.

    We tend to think of our information systems as a foundation layer that support the “real” business of the organization – for example, by providing the information executives need to steer the business and make the right decisions.

    But information is rapidly becoming much more than that: it’s turning into an essential component of the products and services we sell.

    Information-augmented products

    In an age of social media transparency, products “speak for themselves”– if you have a great product, your customers will tell their friends. If you have a terrible product, they’ll tell the world. Your marketing and sales teams have less room for maneuver, because prospects can easily ask existing customers if your product lives up to the promises.

    And customer expectations have risen. We all now expect to be treated as VIPs, with a “luxury” experience. When we make a purchase, we expect to be recognized. We expect our suppliers to know what we’ve bought in the past. And we expect personalized product recommendations, based on our profile, the purchases of other people like us, and the overall context of what’s happening right now.

    This type of customer experience doesn’t just require information systems; the information is an element of the experience itself, part of what we’re purchasing, and what differentiates products and services in the market.

    New ways of selling

    New technologies like 3D printing and the internet of things are allowing companies to rethink existing products.

    Products can be more easily customized and personalized for every customer. Pricing can be more variable to address new customer niches. And products can be turned into services, with customers paying on a per-usage basis.

    Again, information isn’t just supporting the manufacturing and sale of the product – it’s part of what makes it a “product” in the first place.

    Information as a product

    In many industries, the information collected by business is now more valuable than the products being sold – indeed, it’s the foundation for most of the free consumer internet. Traditional industries are now realizing that the data stored in their systems, once suitably augmented or anonymized, can be sold directly. See this article on the Digitalist magazine, The Hidden Treasure Inside Your Business, for more information about the four main information business models.

    A culture change for “traditional IT”

    Traditional IT systems were about efficiency, effectiveness, and integrity. These new context-based experiences and more sophisticated products use information to generate growth, innovation, and market differentiation. But these changes lead to a difficult cultural challenge inside the organization.

    Today’s customer-facing business and product teams don’t just need reliable information infrastructures. They need to be able to experiment, using information to test new product options and ways of selling. This requires not only much more flexibility and agility than in the past, but also new ways of working, new forms of IT organization, and new sharing of responsibilities.

    The majority of today’s CIOs grew up in an era of “IT industrialization,” with the implementation of company-wide ERP systems. But what made them successful in the past won’t necessarily help them win in the new digital era.

    Gartner believes that the role of the “CIO” has already split into two distinct functions: Chief Infrastructure Officers whose job is to “keep the lights on”; and Chief Innovation Offers, who collaborate closely with the business to build the business models of the future.

    IT has to help lead

    Today’s business leaders know that digital is the future, but typically only have a hazy idea of the possibilities. They know technology is important, but often don’t have a concrete plan for moving forward: 90% of CEOs believe the digital economy will have a major impact on their industry. But only 25% have a plan in place, and less than 15% are funding and executing a digital transformation plan.

    Business people want help from IT to explain what’s possible. Today, only 7% of executives say that IT leads their organization’s attempts to identify opportunities to innovate, 35% believe that it should. After decades of complaints from CIOs that businesses aren’t being strategic enough about technology, this is a fantastic new opportunity.

    Design Thinking and prototyping

    Today’s CIOs have to step up to digital innovation. The problem is that it can be very hard to understand — history is packed with examples of business leaders that just didn’t “get” the new big thing.  Instead of vague notions of “disruption,” IT can help by explaining to business people how to add information into a company’s future product experiences.

    The best way to do this is through methodologies such as Design Thinking, and agile prototyping using technologies should as Build.me, a cloud platform that allows pioneers to create and test the viability of new applications with staff and customers long before any actual coding.

    Conclusion

    The bottom line is that digital innovation is less about the technology, and more about the transformation — but IT has an essential role to play in demonstrating what’s possible, and needs to step up to new leadership roles.

     

    Source: timoelliot.com, November 14, 2016

  • Ten ways to drive value from big data

    bigstock-Big-data-concept-in-word-tag-c-49922318Just think what $48 billion could buy. In the private sector, that could buy a lot of R&D and innovation; the lifeblood of a successful and growing economy. In the public sector, think of the boost it could give to education, healthcare and defence.

    What is that figure and why is it relevant?

    According to a new report from PricewaterhouseCoopers, that is the sum of money the Australian economy left on the table last year and wasted due to its inability to fully leverage the potential of data-driven innovation.

    $48bn: that’s the equivalent of 4.4 per cent of gross domestic product and about the same as the entire (and struggling) Australian retail industry.

    Little wonder that big data is top of the CIO priority list on almost every report you read. So why then do people still question the value of big data?

    The challenge is that, while the principle of getting value out of all the data that is now available in the world in order to gain new insight, better serve customers and find new markets seems simple, doing so is actually hard in practice.

    How do you realise commercial value from your data and not end up on a hunt for fool’s gold?

    1. Realise you’re on a journey

    When you begin to seek value from big data you will need a healthy degree of realism. It is hard to get to a revenue stream right away. More likely it will be a journey, starting with projects that add value to the existing business before arriving at opportunities that create whole new revenue streams.

    A good starting point is to leverage how you already make money. Consider your current revenue streams and how you could approach them differently to add new value, and what insights will be required to achieve that.

    2. Do you have the right team

    It is common to get caught up in the excitement of big ideas, but are you ready for it? It’s not to say the concept won’t become reality, but in many instances, it may become apparent that you are six-12 months away from it becoming viable.

    From experience, those companies that have gone at projects too early have failed to realise the value, and then stalled in their big data activities as a whole due to the failure, or have given the idea away in their attempts. A key element of being ready is having the right team in place; that is tenacious, will persist in the face of various obstacles, brave enough to take the initiative, and inventive being able to create new value from data.

    3. Selling your data could be like selling your soul

    As big data skills are in short supply, some companies decide to sell their data and achieve revenue from it that way. Unless you understand how you could monetise your data yourself, you are at risk of commoditising your own information.

    Before you go this route, focus on figuring out how your data can augment your unique value proposition, and don’t give up on creating new value from your data just because the first experiment doesn’t work. Also be aware of the potential risks of selling your data or the insights into it. These include issues around the security of the data once it is no longer under your control, the chance of re-identification of anonymised information, and the potential impact on your reputation if it is used for unintended purposes.

    4. Is there a wider ecosystem you could be part of?

    There are, however, increasing instances of companies and industries collaborating around, or selling data. For example, in the pharmaceutical industry we have seen organisations working as a consortium around the creation of new data sets from clinical research, as a way to overcome the prohibitive cost they would have faced doing it alone.

    The advice here would be not to rule options out — especially if they might enable you to do things with data that you couldn’t do before, and as a result, move up the value chain or closer to the end consumer.

    5. Don’t chase fool’s gold

    Use data, and especially social data, wisely. While providing great insight into the digital DNA of customer decision making, developing accurate models for sentiment analysis is hard, due to the large amount of false positives that exist.

    The nature of social means that many companies, at any time of the day or night, can have somebody saying something negative about them. How do you know when is this out of the norm?

    This level of understanding is something that often develops over time, and is an enrichment and maturity process in your analytics. Get it right and you can make money by developing an understanding of the soft signals, but unless you have a historic wealth of data in that area, gaining that sort of intelligence is hard to come by.

    6. Understand the customer contract

    You need to know what your trust relationship is with your audience. At the advent of the concept of 1-1 marketing, the customer understood the idea that by giving a bit more information they could get a more personalised treatment — and they didn’t mind it.

    However, with the arrival of big data, some customers feel that companies are going too far in collecting and using intimate details gathered without their prior permission. It also depends on the company.

    Customers expect the likes of Google and Shazam to use data to make recommendations. You just need to understand where the line needs to be drawn.

    7. Realise the goalposts are always shifting

    Change is inevitable and rapid. Your key competitors today may well be superseded by companies you never dreamt would fit in your market. However, it’s not all about the big guys. The internet of Things is going to be a great leveller, particularly in the field of ‘controls’ which is enabling new, smaller players to nip in and seize customer data and ownership. This is giving them the power to disintermediate traditional providers.

    8.Be prepared to unlearn

    In some cases you might find that the data shows that your assumptions are incorrect or that your activity is not the success you hoped it would be.

    For example, many companies seek to make money from content, but analysis shows it is a highly crowded market and there is little money in it other than for the likes of Google and Facebook.

    Companies need to understand what the implication is for their business. Does content add value to your customers, is it expected by your customers? Rather than there being money in the content itself, is there value that can be derived from better understanding the digital signature of your end users in being able to see what caused someone to click on an ad or what sort of people are visiting your website?

    9. Don’t confuse perfection with monetisation

    This is extremely important. When programmers and IT people talk about data, they often talk about perfection because we are very deterministic. We want to say ‘if this, then that’; if you get this data, then you will achieve exactly that result.

    It is hard to achieve perfection. Consider s case where you find you can cut the cost of a process by 30 per cent in a relatively short time frame. Or you might have the potential to cut your costs by double that, but it would most likely take you several years. Is the wait worth the lost opportunity cost? In a big data world, the best practice approach would be to experiment — try something and iteratively improve it instead of trying to get perfection out of the gate.

    10. Remember, David doesn’t always beat Goliath

    while new entrants can outmanoeuvre established organisations, most often David doesn’t beat Goliath. In fact, as often, the incumbent can use data to create barriers to entry, due to the fact that they have a significant advantage from the large volumes of historic customer information and transactional data they hold.

    However, to realise the benefit, established operations need to digitise or datify all of this information before their rivals do, and potentially seek out new data streams to compliment what they already have.

    For new entrants, many of the key business opportunities exist where there is a breakdown in a process or supply chain in an area that really matters to the customer — think Uber or Airbnb. Look for what is ‘broken’ in areas that are not already heavily digitised.

    The reality is that there is a whole range of data out there, offering new ways to get insights, drive value and compete. It is essential that you understand the potential and get excited about the opportunity. Think really broadly about the data that is out there, both inside and outside of the organisation, see what there is that could add value, without ending up on a hunt for fool’s gold.

    Source: The Australian Business review

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