Organization Data-driven Building A
BUILDING ADATA-DRIVENORGANIZATIONHOW TO LEVERAGE DATA TO GROW YOURORGANIZATION LIKE NEVER BEFORE
IntroductionData does not make decisions – people do. Having all the relevant data in the worldmakes little impact if it is not properly leveraged by decision-makers. Conversely,having dedicated, data-driven leaders in every key position of your organization willhardly matter unless the right data is made available. This e-book outlines theprerequisites of a true data-driven organization – and the critical steps towardsbuilding one.In today’s digital economy, data is an incredibly valuable resource. While many refer to dataas the new oil, we prefer to think of it like water.Like data, water is everywhere. We find it in the greatest of oceans, lakes, small ponds – andeven inside us. But while it might be everywhere, it takes on several forms, and variesgreatly in purity. Clean, consumable water is scarce. This is also true for data.They also both flow – some quickly, some slowly – finding the path of least resistance atevery turn. Every data manager knows that if you want to make sure data from the rightsource ends up at the right place, you need to plan this flow carefully . And along the way,you better have proper treatment facilities ensuring its quality – muddied waters alwayslead to bad decisions.So the question is rarely whether or not your organization has data. The question is: Whatdoes your organization do with it? Do you let it wash away, or do you create the necessaryreservoirs, treatment facilities and distribution networks to harness its true power and –give your organization access to something they can use? And finally, do decision-makerstrust its purity, quality and authenticity?1
Why a data-driven organization?There are numerous advantages to being a truly data-driven organization. At its core liesgaining a competitive edge through better decision-making and increased efficiency. Adata-driven organization can simultaneously increase revenue and reduce costs, all thewhile bolstering the quality of products, reputation and organizational processes.Increased revenueThe mechanisms through which this happens, are many. First of all, a data-drivenorganization can trust that it always makes informed decisions upon a foundation that isalways reliable and up to date. As such, you remove whim and guesswork from theequation, while simultaneously negating the garbage-in-garbage-out problem.This means data can fully function as decision support for operational systems andprocesses, which can range from sales, production and marketing, to maintenance, logistics,service delivery and other industry specific needs. A data-driven approach also allows youto more nimbly adjust to market changes, responses and feedback – streamlining yourproduction, and accelerating time to market.Additionally, a data-driven organization paves the way for being more innovative, proactiveand agile, letting the data reveal new business opportunities for which to adapt. On top ofthis, the organization frees up human capital that can be allocated towards efforts ofcreating additional value.Reduced costsWhen operational, administrative and decision-making processes are powered by data,you also empower your employees, equipping them with the tools to increase theirautonomy and strengthen their decision-making foundation. This allows for a leaner,more efficient organization – and reduced dependency on external assistance.Cost of doing business can also be reduced directly through more efficient, data-drivenprocesses – both administrative and operational – such as overtime or inventorymanagement.2
Increased qualityQuality in this context is highly connected to accuracy in decision making, sustainability andreputation.More data-driven, and hence more qualified decisions, run all the way through yourorganization, ensuring:1increased trust2improved environment, health & safety (HSE) procedures3fewer deviations and reduced loss during production4increased product quality5increased customer satisfaction3
As for corporate reputation, having precise, actionable data available – and the know-how toapply them – allows you to:1make better business decisions that in and of themselvesenhance reputation2more precisely communicate with target audiences, wheremarket data are available, strengtheningorganization-stakeholder relationshipsAt the same time, there is a strong signaling effect in being at the bleeding-edge of what isoften referred to as the fourth industrial revolution. Being a truly data-driven organization, adriver of innovation – and loud about it – increases brand awareness, augments marketsentiment and attracts tech-savvy, aspiring young talent.DID YOU KNOW?Over 90% of all the data in the world was created in the past 2years; The total amount of data being captured and stored byindustry doubles every 1.2 years4
Ready to take the next step?BI Builders helps organizations become data-driven. We combine powerful data platformautomation with industry experience to improve decision making, reduce cost, andaccelerate productivity.Get in touch to learn how155
What exactly constitutes a data-drivenorganization?A data-driven organization manages data in such a way that it creates a single version of thetruth. This means and requires that the data is both relevant, reliable and available.Furthermore, this data is then used as a foundation for making business decisions.The way we see it, the foundation of a truly data-driven organization, rests on these threepillars.Data-driven OrganizationBusiness StrategyHolistic andRelevant DataAvailableData Strategyand DataGovernanceCulture &CompetencyTechnologyIllustration 1: Data-driven organizationWe will explain what each pillar means, why we consider them the building blocks of adata-driven organization, and provide pointers on how to construct them in your ownorganization.6
Business strategyWhile technically not a pillar, you can consider this the support beam to which all other pillarsare attached. There is more to this than just architectural soundness.Building a data-driven organization must be rooted in your organization’s business strategy.This means both clear budgetary allocations and leadership involvement. It is crucial at thisstage to start with your business needs, not technology. The main challenge is almost never alack of tools or technology – it is knowing how to leverage what you have at hand to createadditional value or a competitive advantage.In our experience, you need to start by asking the following key questions: What are the most pressing business needs to which more and better data could be theanswer?What is our actual level of ambition when it comes to gathering, storing and sharingdata?What KPIs are relevant going forward?These are questions that need to be answered at a strategic level. Again: At this stage youshould be technology agnostic, and remain laser-focused on your actual business needs.Furthermore, our experience is that corporations tend to narrowly target their budgetaryresources into procuring and implementing technology – neglecting needed allocation to theother two pillars. It is not about technology alone. Technology is primarily a foundation – anenabler. Modern tools and technology will not by themselves automatically result in adata-driven organization if the users cannot or will not use them.“Without data you’re just another personwith an opinion”W. Edwards Deming, Data Scientist7
Holistic and relevant data availableMost organizations already have a wide variety of data available already. Some are internallysourced, others external. They will be structured, unstructured, and somewhere in between.Volume and velocity will vary.So what do we mean by holistic – or relevant, for that matter? When we say holistic data, werefer to data that concerns the whole organization – across all organizational silos andlevels. Remember the single version of the truth we talked about? This shared insight isconstructed first once you are able to paint a complete picture across silos like ERP, CRMand operational data.Holistic data spans the entire organizational value chain, from operational data such asorders and deliveries, to controlling, financials and other administrative data.As for relevance, we consider this a key data quality aspect. Essentially, it means the rightdata, at the right time – for the right purpose. And consequently: how well the data cansupport a specific need or decision.Based on our experience, it is once again important to start by mapping out your data andbusiness needs and priorities. Keep in mind that most data use cases fall into three broadcategories, with the timeframe as a key separator: operational decisions (seconds, hours,days), tactical decisions (days, weeks) and strategic decisions (months, quarters, years).Strategic decisions typically address high-level goals related to growth, profitability, HR &employees, regulatory compliance and sustainability. Tactical decisions are typically aboutwhere to focus resource spending and how to detect new opportunities ahead ofcompetitors. Pure operational decisions could be everything from monitoring criticalprocesses for a production facility to speeding up the application processes for amunicipality.Additionally, your available data might be more or less relevant to the extent that they cannurture R&D initiatives. Examples of needs driving innovation measures could be related toa company’s deliveries, like product development, price elasticity or supply and demandmatching – or customer relationship management.8
Data strategy and data governanceThere has never been more buzz around transparency, data sharing and open ecosystems.Simultaneously, concerns around privacy are growing, and we are dedicating ever moreresources to building sophisticated methods of access control. In a way, these forces areworking against each other. At the same time, it is apparent that data governance is more thanjust a fad – becoming increasingly relevant for every part of the organization.This means that whatever data you are collecting, structuring and acting upon, you need crystalclear governance rules. These rules are necessary to meet regulatory compliance, and could forexample govern how we share and work with data across the organization.Data strategy needs to be anchored at the very top of your organization. In our experience,governance rules should be detailed as leadership develops its business strategy. The threepillars plus technology, however, represent the implementation of this strategy relating to theuse of data as a strategic resource.9
Culture & competencyThe graveyard of data and analytics projects is filled with great ideas. We have seen the proofof concepts, the pilot projects and the headstrong initiatives. Many of them are superb – onpaper. The payoffs seem bright as day, the ROI is a no-brainer and the technology is sound. Eventhe implementation can seem smooth as butter.And yet, months later, the tools are collecting dust – before the project gets shelved altogether.What on earth happened?More often than not, the problem is that the organization simply was not culturally prepared.Yes, becoming a data-driven organization is partly a data, strategy and technology project, but itis just as much a change management process and cultural project. If you want user adoption,you cannot forget the user.In our experience, it is crucial to remember the importance of leading by example. Leadersshould, whenever possible, actively use data to substantiate claims, decisions, ideas andbusiness cases.Becoming a data-driven organization also requires a certain level of digital maturity orcompetency. However, you cannot simply give every user a crash course and expect lastingchange. This shows how culture and competence are closely linked. Knowledge expires, andchange in people’s behavior takes motivation and time. If you want to not only get ahead, butstay ahead, you should aim for a curious, data-driven and data-seeking culture – drivingcompetence forward continuously.DID YOU KNOW?If you burned all of the data created in just one day onto DVDs,you could stack them on top of each other and reach the moon –twice.10
One way of fostering this is to schedule regular data-competency training sessions across theentire organization. As the landscape is rapidly changing, having such a culture is a necessity ifyou want to keep the competitive edge that being data-driven provides.The very first step any aspiring data-driven organization should take is to map out theirorganization’s digital maturity. Where are we right now in terms of culture and competency?And subsequently, how does this map onto our level of ambition as decided in the businessstrategy?Whatever disparity is there, highlights the path for which educational or culture-buildingmeasures to implement – whether it is training, inspirational workshops or motivationalstorytelling.Secondly, zooming in, there is a second gap between what users expect from IT – and what ITexpects from users. With leading tech companies such as Google, Amazon, Facebook & Applesetting the bar for ease of use, data availability and relevance, users might expect tools to bequick, reusable, simple to understand – and providing a clear answer to their businesschallenges.IT, on the other hand, might expect users to not only be able to procure data and analysesthemselves – but use these without needing guidance.In our experience, the most important answer to this is building a culture where mutuallearning and understanding is a core principle. Only then can you maintain sustainablerelationships between disciplines – and have the data-driven culture really thrive.11
Attempts to close this gap have also paved the way for self service BI, essentially tools thatmake it easy for every user to access and draw key insights from data – without having toconsult the IT department.But even with easy-to-use tools, the key questions remain – and they need to be answered: What use cases do we need these tools for?What types of data can give us the insights to make better decisions – or operate moreefficiently?What available tools can actually give us the relevant data?Who in our organization has the right skills and motivation to use this data?How can we set realistic expectations for both people and software?Keep in mind that there might be gaps within all 3 pillars, and they might vary acrossorganizational departments and levels. These gaps are never filled by the click of a button, butthrough gradual changes over time.12
To sum it all upA truly data-driven organization manages to use data both as strategic, tactical andoperational decision support – and to create more efficient business processes.This is made possible through clear data strategy and data governance, havingholistic and relevant data available, and by fostering the right culture & competency.All of this needs to be rooted in the organization’s business strategy.With all of this in hand, we wish you good luck on your path to becoming moredata-driven!Ready to take the next step?BI Builders helps organizations become data-driven. We combine powerful data platformautomation with industry experience to improve decision making, reduce cost, andaccelerate productivity.Get in touch to learn how1513
A data-driven organization manages data in such a way that it creates a single version of the truth. This means and requires that the data is both relevant, reliable and available. Furthermore, this data is then used as a foundation for making business decisions. The way we see it, the foundation of a truly data-driven organization, rests on .
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Becoming a data-driven organization The what, why and how Ongoing digitization has created vast streams of data, forcing businesses to become more data-driven than ever . get better insight into customer behavior, or begin with productivity data from the shop floor. Or, recorded customer service calls or data from your .
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into a data-driven organization" or "become more data-driven," most organizations struggle or lag when it comes to acting on a data strategy. With an end-to-end data strategy, you can manage the growing volume of your data, uncover insights across a variety of data types, and make it readily available to the right teams and systems.
Foundations of a Data-Driven Enterprise This book is divided into two parts. In Part I, we discuss the theoret‐ ical and practical foundations for building a self-service, data-driven company. In Chapter 1, we explain why data-driven companies are more suc‐ cessful and profitable than companies that do not center their decision-making on data.
Contents Part One Introduction 1 1.1 Data-driven organization design 3 Effective organization design and management 5 Why people are struggling with organization design 6 How this book will help you 8 Structure of the book 10 Final thoughts 10 Notes 11 1.2 Challenges 13 Introduction 13 The reality of the challenge 14 Common challenges in organization design 17 Final thoughts 23
Table No. 2: Data Driven Testing . Data Driven Testing Tools - Parameters QTP LoadRunner WinRunner Junit . Access data from external source 5 5 5 - Change the data without effecting script 5 5 4 - Way of testing 5 4 4 3 . Data Driven Testing Quality. 5 4.6 4.3 0.33 . It clears that QTP is excellent data driven testing quality followed by .
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