Data: the Art of the Possible How to Create Value from Your Different Data Sources

Data: The Art of the Possible How to create value from your different data sources

Creating value from data is a journey. Preparation for that journey is crucial and involves identifying all the core data sets and getting them ready for analytics. Only then can the process of extracting value from them run with maximum efficiency. Preface

As the ancient Chinese proverb says, the hardest part of the thousand mile journey is the first step. There is no more daunting journey than a 23% mountainous shifting landscape that grows bigger by the hour. Yet, that Only 22% of businesses closely align is an accurate summary of the task involved in managing your data and overall strategy with available data. getting the fullest, most up to date and informed intelligence possible.

Having managed and analyzed data for the best part of a decade, Rosslyn Analytics has seen the best and worst of practices and absorbed the lessons, so it can help companies maximize their application of information and intelligence throughout the organization.

All organizations run on data, but their ability to successfully exploit it is dependent on many variables, such as data quality, access to information, timeliness and relevance. Though all organizations have a common heritage in their reliance on data, the way they plan, adopt and use data varies dramatically.

We believe that the old fashioned, non-scientific approach to data is akin to the dietary ignorance that impeded the growth of previous generations. The lack of understanding of the potency of data, and its ability to invigorate every organ of the organization is symptomatic of a wider malaise.

In the next sections, we will explore these themes and create a road map for the journey to invigoration. In doing so, you will be able to ensure that your organization will not become one of the 33% of Fortune 100 organizations Gartner estimates will experience an information crisis by 2017 due to their inability to effectively value, govern and trust their enterprise data.

Hugh Cox Chief Data Officer Rosslyn Analytics

2 [email protected] www.rosslynanalytics.com The Value of Data

This paper has been designed to Business and technology leaders often fail to question the importance of data or even why they serve as a reference guide to help should implement a data management program. However, there is a gap in perception and reality of best practice and what is going on in the business today. In other words, many theories so few you make important decisions; practical examples. those where you are not sure where to find the answer in all the data What is missing is HOW to put in place a plan of action. A successful plan only comes from your organization currently has – knowing the value of data, as it will enable organizations to prioritize resources and investments. but isn’t fully using or exploiting. This paper is a first-of-its-kind. Unlike McKinsey, we don’t estimate the theoretical value of big data in the pharmaceutical industry, for example. That won’t solve your immediate problem of reducing the cost of drug research and development, or improving your ability to mitigate supply chain risks.

This paper has been designed to serve as a reference guide to help you make important decisions; those where you are not sure where to find the answer in all the data your organization currently has – but isn’t fully using or exploiting.

This paper will also come in handy when you want to tackle a specific business problem or explore a potential market opportunity; as you’ll be able to discover new insights and solutions that arise from the marrying of different data sources together.

To help make the meaning and value of data easy to understand, and to make it personally Value of data relevant to you, we compare data to food groups. There are, after all, similarities. You sometimes Employee data need a nutritionist (or doctor!) to help understand what to eat and when in order to perform in a manner that suits your lifestyle and goals.

+ All organizations (whether small to medium sized businesses or global pharmaceutical giants) Salary benchmarks must be sustained and fortified by a constant intake of data. It has to be useful and in the right proportions. The intelligence each needs differs, but the requirement for a balanced diet unifies all organizations. No matter how many suppliers, products or customers they have and in what proportion, they will still need some combination of the six major data food groups: customer, Effectively= recruit employee, product, financial, spend and supply chain data. and retain talent The devil, however, is in the detail. This white paper is intended to explain the most important general concepts underpinning the Value of Data, and provide a framework by which you can plan and execute business and data strategies. This paper will provide a start point for a planned, sensible data intake and a course of invigorating exercises that will enable all companies to work off that information, keeping the enterprise lean, agile and healthy.

3 [email protected] www.rosslynanalytics.com We have millions of lines of complex data, coming in from multiple sources and Rosslyn Analytics’ RAPid platform makes it simple for us to analyze and manage, allowing data driven strategic sourcing decisions every day.

Jenny McGeough, Value Chain Excellence Project Manager, The Weir Group PLC

Problem Definition

In the rush to analyze all the information at hand, many organizations Value of data go boldly, but blindly, into a blizzard of data and soon become lost. They need to get their bearings before they begin. The founding principles Product data of a good data strategy revolve around:

+ 1) Obtaining data-business alignment; Commodity prices 2) Understanding the alchemy of data: and, 3) Improving data quality.

Improve= profit Let’s explore these three areas in greater detail. margins by leveraging fluctuations 1. Data Alignment Data alignment is a tragically overlooked but vitally important key to wellbeing. It’s vital, and it should be the first step in any analytical effort because poor data-business alignment leads to poor decisions – not to mention costly data and technology investments; this can happen when a company puts too much weight on one entity without looking at the interdependence of all departments of an organization.

It is no good if the senior vice president of a large manufacturer spends millions of dollars to create a lean supply chain operation if that leads to underfunding in other areas such as, say, sales. If customer revenue falls, then that impoverished department will be asked to make even further savings on the supply chain, because there will be no money to re-invest in the business. The problem being, of course, that they have already produced the leanest possible infrastructure, which means that any more cuts will start hitting the bone.

4 [email protected] www.rosslynanalytics.com This exemplifies how company data strategy can go off course, as goals are hastily set without understanding and creating the alignment of the business to information. This guidance can only come from the understanding and management of data with desired business outcomes.

44% The realignment of organizations around data is difficult because it requires significant see data as a strategic asset organizational change. It calls for a new focus, from the top down, and discipline from the bottom up.

As a starting point the enterprise leader should assess the organization’s goals (the use case of data). The next step is to determining what type of data they believe is required to make those decisions. This also works the other way around: you may have a specific type of data which will help determine the correct business goal. The key message is aligning both of these points – data and business goals.

Diagram 1

Align data to your business goals Align business goals to data

Internal + External Type of social- External data (=) Business Business data type data type demographic data sources Answer Goals

Customer data + Social-demographic Geo-location Credit card + Boost campaign Increase sales companies effectiveness by revenue targeting the right groups of customers

Once the value of data is established, it often comes as a shock to discover that copious funds have been wasted on unnecessary business intelligence or analytical projects. Meanwhile, other areas of the business will have been kept in the dark through under investment in data.

According to Forrester Research, 90% of the data sitting in most organizations is not used Value of data primarily because it is so difficult for people to access, they fall at the first hurdle.

Customer data So a large percentage of problems persist and go untackled, and a number of opportunities go begging. However, once the data is accessible, you can improve its quality and your organization + will benefit from better, more timely, decision-making thus trust and value your data more. Customer behavior 2. The Alchemy of Data Once you know what you want to achieve in terms of business objectives, you will be in a better position to understand the type of data you need to support your decisions. Reduce= marketing spend on low revenue making All types of information becomes much more powerful when contextualized. Data sets, when customers cross-referenced, become even more so. This multiplication of value is created due to a certain alchemy that exists between different data sets. The more you mix together, the better the outcomes – increase in profitability, business efficiency and internal alignment.

5 [email protected] www.rosslynanalytics.com Rosslyn Analytics believes every organization should follow a three-phased approach to data 41% discovery and analysis: say data is from too many different sources. 1 2 3

Obtain and use Connect multiple Connect internal specific internal internal data data with data sources sources into external source a single view of information

It is not uncommon to see organizations run expensive, year-long big data projects that incorporate phase three before they’ve mastered one or both of the first two phases.

In the long-term, this approach is unsustainable because long-term business performance will be impeded and reveal which organizations have not focused on exploiting the value of their existing data. This leads to a situation where business value goes untapped and organizations are missing opportunities.

The question is where efforts should be focused most profitably. Fortunately, we have provided use cases of data for every major department with practical examples of: Value of data • When to apply data to solve business problems Product data • How to get the most out of existing datasets within your organization • How to augment your decision-making with contextual information from external sources

+ Below, in each data section, you are given an overview of how you can exploit the value of core Competitive intelligence datasets, at each phase of the journey, so you can maximize your efforts and investments.

= 3. Data Quality Secure first mover status For obvious reasons, bad data taints the thought processes of any organization and leads with new offerings to inefficient – and sometimes disastrous - decision making. No matter how wonderful your visualization tools and your data mining platforms – ‘garbage in’ still leads to ‘garbage out’.

It’s also costly! According to Experian, 75% of organizations waste an average of 14% of revenue due to poor data quality.

The techniques many organizations currently use for refining the quality of data (such as removing bad records, deleting duplicates and incomplete entries) are not enough.

However, more importantly, it’s a reflection of how organizations view the value of data and where they are using data. The more that data gets used in decision-making, the more perceived value employees get out of it, and, as a result people are more concerned about keeping it in shape.

6 [email protected] www.rosslynanalytics.com Value of data Customer data + Customer lifestyle

Reduce= customer churn by creating customer profiles

New World Order: Take a New Approach to Exploiting Data

In order to stay healthy, an organization needs a balanced diet of information on customers, employees, suppliers, products, finance and spending.

Too much of one thing and too little of another can lead to bloating in some circumstances, circulation problems, light headedness and even hemorrhaging of cash and resources. Six We believe there are six critical data When too much sales information is absorbed, without a counterbalance of spending data to food groups that are essential to soak up the excesses, a sales director can become giddy and prone to rash judgment. Under these maintaining a healthy corporate body. circumstances, anyone over indulging like this should be prevented from driving a car, making forecasts or operating any of the heavy levers of power in a modern mobile enterprise.

We believe there are six critical data food groups that are essential to maintaining a healthy corporate body. This section will discuss how they work, why and in what proportions they should be taken. It will examine why some data rapidly perishes, while others have an almost timeless sell by date. We will discuss how you can marry data to bring out its full flavor, and warn against mixing data types that are incompatible.

Below you will find practical examples of data preparation, sharing and consumption which have benefitted users and created a sense of wellbeing and health. These will be tempered with some cautionary tales of data abuse, misuse and malnutrition, as a warning of the perils of taking data for granted.

First, we should explain the form and function of the six essential data food groups that all breeds of organizations run on:

7 [email protected] www.rosslynanalytics.com Six Datasets Critical to Your Success

Customer data Employee data Product data

Offers insights into existing Provides insight into your Is a record of the portfolio that a and prospective buyers of colleagues, past, present and company offers and how the market goods and services. Customer future. Employee data is primarily (customers) responds to it. Product data is primarily a top-line a top-line revenue maker. data is primarily a top-line revenue revenue maker. maker.

Financial data Spend data Supply chain data

Sheds light on revenue and other Provides visibility on where the Tells the story of the sourcing of the incoming transactions. Financial data enterprise’s investments are being essential raw materials, goods and is used for both creating top – and made and what its running costs are. services required to function. Supply bottom-line value. Spend data is primarily a top-line chain data is primarily a bottom-line revenue maker. revenue maker.

8 [email protected] www.rosslynanalytics.com Product Data

This is the meat of the business. Products, like protein, can be broken down into their various components and absorbed into the body of the organization. Products go hand in hand with the strength of a company.

The more products that a company has, in The car maker had pleased audiences for general, the better it will be able to withstand years, but its intelligence told it that consumers adversity, fight off competitors and move were developing a taste for a lighter model. quickly. The company with products targeted So Ford gave them one, by blending various at multiple sectors will always be best placed data ingredients and cooking them, it created to address a new market when it begins an end product that was 700 pounds less to take off. heavy. First it took some aluminum alloy parts and used them to create new components, However, just as too much protein can cause instead of using the traditional iron. This kidney failure, the regulating organs of a meant it could burn less fuel, a saving that corporation can begin to overheat and even could be added to by using a new technique, shut down if they are forced to process too stop-start technology. A bit of data crunching much product information. Since products allowed Ford to source a 2.7 gallon EcoBoost come in many forms and have many functions V6 engine that provided this flavor of motoring (some are outward facing, some regulate experience. internally and others address suppliers) so Value of data it is quite easy for a company to become too The data analytics used to define the product Product data ‘pumped up’. helped Ford make a big difference to its revenues. The lower CO2 levels produced Product data can cover everything from a helped with the product plaudits from + company’s own prices to competitor prices, The Union of Concerned Scientists, the Customer feedback from customer feedback to supplier costs. To Natural Resources Defence Council and the understand how product data can be blended Environmental Defense Fund. As a result of to create a rich, succulent morsel, which both the goodwill generated and the impressive = hits the spot but offers an immensely satisfying performance data, Ford sold over 760,000 Lower product returns by after taste, let us consider how Ford Motor F-150 trucks in 2013. Company presented its F-150 truck to an incorporating requests ecstatic audience of consumers. from reviews

9 [email protected] www.rosslynanalytics.com Creating value from product data

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10 [email protected] www.rosslynanalytics.com Customer Data

This is a very complex information set which has massive hidden consequences and opportunities, much like a vitamin intake. It affects the making of deals and the opening and closing of sales, in ways which aren’t entirely understood by scientists.

It can have a short shelf life – because The lesson of this big data exercise was that customers are organic and subject to rapid the real profitability of products is deceptive. change – and if customer data is overcooked its Taking one value on its own is misleading nutritional value can be destroyed. However, and sometimes other elements can if the data is fresh and used sensitively, it can combine to bring out more. In this case, be massively beneficial. only analysis revealed the true value. Though the margin on a banana might be low, Consider the case of a high street retailer that if it gets the right people into the body building used big data analysis to discover something shops, it’s a marketing tool as well as a unit in fresh and totally unexpected about its clients. the product portfolio. The retailer delved into its information on brand awareness, loyalty, demographics and Analysis of customers also showed that many of the other fields of customer data. frequency of buying doesn’t correspond with By cross referencing them it discovered an profitability. However, it also shows that loyal Value of data unusual taste. The data revealed that the main customers shop more often and spend 30 per buyers for its bone strengthening products cent more per transaction. Those who buy Customer data were not brittle-hipped pensioners but steroid- the store magazine spend 50 per cent more driven young body builders. than those who don’t buy it. There are many actions and reactions at play + Analysis revealed these were valuable shoppers when the chemistry of customer Customer online who drive profit. The bone fortifying food itself data is examined closely. conversations was not a particularly high value product (it was aimed at a demographic that isn’t particularly rich) but it turned out this commodity was = attracting some valuable customers. Lower reputational risk So logically, it was worth pushing as it raised by identifying disgruntled the frequency of these valuable customers and customers attracted high-value shoppers.

11 [email protected] www.rosslynanalytics.com Creating value from customer data

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12 [email protected] www.rosslynanalytics.com Supply Chain Data

Just as the human body cannot produce all its own nutrients and needs a staple intake of minerals by which to manufacture its tissues, so does the corporation need regular supplies.

Supplier data helps an enterprise to regulate A good balanced diet of supplier data is its intake. It’s important that the company increasingly difficult to achieve in today’s knows exactly where to source its supplies, busy corporate landscape. A recent Accenture how reliable the source happens to be at any survey of 1,000 senior executives from global moment (this is subject to constant change companies found that 97% of them understood and risk) and whether there are alternative the value of big data in the supply chain, but pastures that need to be explored. only 17% had an idea of how to implement it – even in a single supply chain function. The supply chain is a particularly perilous territory. In certain industries, such as retail, Examples might help improve understanding. the fine-tuning of the supply chain makes The big four UK supermarkets use big data the difference between survival and death. analytics to investigate losses from their If a CIO can shave half a percentage point supply chain. Much of the produce travelling off the supply chain costs of one of Britain’s is perishable and delays in the movement big four supermarkets, then he or she would of fresh fruit and meat causes companies to achieve legendary status, as the potential throw billions worth of food away every year. Value of data savings would run into the millions. It is an Supply chain data incredibly difficult task, however, as the supply In the vast warehouses of the distribution chains for companies like Tesco, Sainsbury’s chain, as goods make a pan European journey and ASDA are notoriously tight and the from producer to processor to distributor, + managers already run incredibly lean and it is easy for pallets to get damaged or Geo-political events agile operations. misplaced temporarily. Analysis of information gathered by RFI (radio frequency investigation) Supplier data doesn’t just have to be about tags on each pallet of goods and sensors = logistics. It can cover everything from political placed at each stage of the supply chain Prevent supply chain to geological data, from world stock markets has enabled Tesco to gather masses of data to commodity prices. No single piece of on the traffic flows of products as they are disruptions supplier data can single handedly change transported across its global network. the way the body works but, in combination it can catalyze important reactions that This knowledge – about accident black spots, energize the enterprise and restore the black holes into which goods go missing and profitability of the corporate body. time consuming bottlenecks – has allowed Tesco to save millions by ironing out these discrepancies.

13 [email protected] www.rosslynanalytics.com Creating value from supply chain data

Key KEY Impro Supply chain data Supply chain data ve s upp tcome: accuratel ly c Data from other internalData departments from other internal departments chain ou y buy the ha upply righ in S ock to support marketin t de External data External data es of st g prom cis ntiti otio ion qua id holding stale stock post p ns Sup s Business outcome Business outcome o avo romo ply b e nd t tion ch y c us a un ai o a k sta n o m c oc rom other inter bl ut b ot st data f nal dep r e v co in o with artm isk en m in r ow ata en y s do e: g he . l n d ts a up rs id s t g ai n pl a en u y e. ch d/o ie nd t p f - ly r rs t ify p ti s p ex b a h ly n s e up te ef ke i re ri s Product demand r or s gh c e e e n e t h id u v in al th ep e a : ig li b t d e s xp in e f e m uc a s to e s o d ta u n d m e d C ro p re d a l e p p p it t o a t e ly l u a c a h D a r t s l t t ia u ch c e w g u d c n a e w u r o e o t it o n o m m & in h i h i b l e th s a ia rketing campai p B is m in s c Ma gn a r p f o e l t o n a in t l n s y d u w h a c e ectation s t a e in exp s fi t a it n e S m s n r t h c r d a e i m ie t e r le a f f r u n is l o o e o c t k s l o c v b S i s y r g li a ts up a m n e ta in p ls ri d a la li s d p e o o d r r it m s f n e o n a t o S d c u u n a o r b t p f e e r h c c e p t M e l ho i i l a o m are us n n e y l W m o g g r s a t c d a e s C s h e n r u nventory e a i l u e i i c s v n e f m m S u e a i p o o d r o c ata u t h n d e e t m a a t e n n d u t r y c s e o r a a d , r a t o a t t o l i a n u t y m W d S n s s g a n c g i h d e e s r n p u i v i h : r e p p G m o u c in o p i p w v c c e i r t h e o i i o i o c s g n s n o r c s a a t a f n g - e t a t e p a s p e o S r r r t d i a n e a n o e r Combine u t p o a i r a n a

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14 [email protected] www.rosslynanalytics.com Finance Data

Financial information is the carbohydrate of the data food groups. It is finance that provides the energies – such as the motivation for staff to go to work in the morning, for customers to buy products, for companies to take the risk of creating products for trade – that power every form of transaction in a commercial enterprise.

Like the complex range of sugars that make up In biopharmaceuticals, they use data alchemy the carbohydrate family, the smorgasbord of to put the most efficient processes in place financial data types is broad, varied and not to make vaccines, hormones and blood universally understood. As with many trendy components. These end products are made short-term no-carb and low-carb diets, many using live, genetically engineered cells, whose agendas based on financial data are myopic, working environment must be delicately short-termist and can be self-defeating in balanced by monitoring and managing over the long run. This is because many types of 200 variables. Two batches of hormones, financial data are as characteristically different produced using an identical process, can as cellulose and glucose. still result in a total variation in yield. Big data analysis is the key to managing yields, Some information can only be digested by maintaining purity and avoiding regularity certain types of beast, others can give a rapid scrutiny. Not to mention profitability. Value of data release of insight but need to be converted into Financial data other forms before they can have long term Biopharmaceuticals makers use advanced strategic value. Auditing and governance data, analytics to boost yields in vaccine production for example, are long-term forms of information without additional capital expense. They do + that need a wider historical analysis. But this by breaking down the entire process into Pricing information quarterly (or even weekly and daily) revenue segments of related production activity. In each streams are examples of data that needs division the finer details about process steps, immediate analysis. materials used and by-products created can = be measured and stored in a central database. Determine how sales Many organizations are supplementing their big data analysis of their petabyte silos of Statistical analysis of upstream and should use discounting information with technology that intercepts downstream process parameters and their with customers data streams as they move across the impact on yield, their influence on the time to company network. Companies such as Storm inoculate cells and the conductivity measures and ElasticSearch provide tools that tap into associated with certain chromatography steps, electronic trading events as they happen yielded enough clues about the potential for and create an instant analysis. This allows improvement for one manufacturer to save companies to make timely interventions if a $10 million a year. That ten million dollar downturn in trading circumstances is identified. breakthrough, as a result of big data science, Companies that cannot process information was the saving on the manufacturing of just efficiently exhibit a form of data diabetes one of its products. that needs to be addressed.

15 [email protected] www.rosslynanalytics.com Creating value from finance data

Key KEY Im Finance data Finance data prov e fin Data from other internalData departments from other internal departments identify new anc utcome: global te e d External data External data nce o rritor ec Fina to expand the business ies isio ns Business outcome Business outcome Fin by ho a co w d nc m le an other intern e o b p s ta from al depa ut in eo es h da rtme co in p in wit nts pr m g s s ey ta an o fin le u n da d fi e: a a b o ce /or ts d n s e n e a e c y th t m ina xte s t e if s f al economic re r w er d t to o ne egion ports na e m a n e c bi R l l t e t ly da l a in a id u p om ta s e w : b C r h i e i im e th tr s es Lif v o m n s e e w o o nu cy t o o h o cl n t h tc c b e u o e y w d otentia v e r u l e n P l al s im s o e s a u f v es e p o R i o i ket/custom o r t h r mar ers f r m H i t la c o s a O u v s o s p n e s e o p e o ra t e rs se t o f y e r io m d o p v n l s ic a e a p le e l r t c c s a m sa u o E r s s e e to t t m s a p t r t o s i nd u e e f nt a tilit r t n o Re y s n c g r e i P e r costs In g a e r p c F r p r o h e m i n r n o e u o e c i c m n s v in r e a m e e g h a n e v n o p u c e s h t e c w E C R e b t g s l m e s - o t u a a n s e i D m e c o p r t c e i g r I a u r l u e c n p r o i i v n e a n e k r t t e r a v e y p d r e v c t r & r e t e Combine r a

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16 [email protected] www.rosslynanalytics.com Employee Data

If departments are the organs of a corporation, then employees are the lifeblood equivalent. Some are red cells, with their capacity to oxygenize the raw materials of production and take them to a higher state of energy level.

In corporate terms, this is known as adding They want to identify whether traders are value. Other types of employee carry out a covertly contacting clients and illegally profiting more regulatory function, with accountants from doing so. Banks also monitor mobile and compliance officers and security having phone use and use data to log the number a role of neutralizing dangers, in the way of times traders take a break to smoke outside. that a white blood cell is devoted to engulfing They do this to identify suspicions patterns anti bodies that make it into the environment. that hint at insider trading.

Employee information as a food group has a Banks must use big data for staff surveillance dual role then. It can help both to oxygenize because the penalties for insider trading are those areas that need life breathed in to them, huge. The scope of surveillance needs to and neutralize others that need to be stifled. be tempered with the potential damage Which is why employee information covers this does to employee relations. The legal everything from selling to social media. issues are another concern. Value of data Banks now track employee data and combine However, employee data analytics aren’t just Employee data the various strands of information to get a based around punitive examples. Employee flavor of the atmosphere on their trading floors. motivation and subsequently retention is This helps them stay within the right side another important area that can be improved + of the regulators. by analysis of the records. Tracking, analyzing Social media network and sharing employee performance metrics For example, some banks monitor their traders’ can give performance data to employers and performance against the number of times help employees get on, by pointing out what = they use internal communications systems. they’re doing right. Helping them to focus their Cost effectively attract attention on the most useful actions is very new employees motivating and maintains employee loyalty. and customers

17 [email protected] www.rosslynanalytics.com Creating value from employee data

KEY Key Imp rove Employee / HR data Employee/HR data HR d ecis Data from other internalData departments from other internal departments ion tcome: retain emplo s b HR ou yees y c External data External data ith the right salaries om w bin Business outcome Business outcome HR in s o g ee ho utc em oy w om p pl om other interna mu e lo m ata fr l depa t ch : r ye f e ith d rtm he e ew e o s ta w ents y a m a d k r da a re pl rd at is to ee nd r o t a r ti oy ry surv /or at ye h w e e pl Sala eys e ed e e i h p m xt s ri th t m e er an ar g te o e Nielsen Glassdoor S n d e h o a c in . AC urve al h p t th b (e.g y) S d o a ta e ig to m u a w i l r it o g “W rv ta d e g C e in h e e a n fo n c n o y g t r m i n pe d s a b m : t e o o - a e i y e c lig rs ) t y s c n s e l o s o o k t s i m f te it on g u in iv t d o o e n t ti et g g e h e f d i e a h o n d c r p c e a th o t t to m lo petitor sala l to l w i a u i e Com ries p l e f t t co a in e y y a o e m n m h i p g a ia d x a i n R in s d S d p r g g m t e e a s lo e h H o is h l u e l C x t l m ar p p y y e n ia s ie p a e / i c te s o r e w s o a a r t s e s d n t m e c e p d ? n i ” e . e u b n u y s o H .g o o t n l tu n (e p a u d R t ries a s e m s Sala nd e o r u E s s p t onuses t n b c io e a t 3 o c f 6 r n n e 0 m fa s e ° s d o y d o s E i i i e b e t n n t v a t m a r : c g : a a u S u k P i d e s w p l c t o s r i e l t h e o o e o b y m l d e n r l a e y

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18 [email protected] www.rosslynanalytics.com Spend Data

Spending, like fat in the human diet, is an essential ingredient of corporate life. However, too much of it is very dangerous and can lead to a rather unattractive bottom line, which will put off investors and horrify auditors.

To learn more about this Spend data is often used by procurement to Tail-end spend exposure type of data, read assess what has been bought, with whom and The quickest savings opportunities can be at what price. Yet, spend data, by connecting had by getting a grip on the biggest spend with How to Obtain a Return on Your it with other sources of information can your biggest suppliers. Yet, the largest savings Spend Visibility: A User Guide transform an entire organization; not just are often found in the tail – the 20% of total for Finance and Procurement delivering bottom-line value such as improving purchasing spent with your smaller suppliers. Professionals. profit margins, the same data can help inform The challenge for many organizations is first decisions focused on top-line goals such obtaining visibility of the fragmented tail-end as increase revenue. spend followed by effectively managing it to conclusion. Here are five real-world examples of the benefits of spend data: Overpayments Unplanned overpayments are inevitable Contract compliance but if it happens more frequently it’s a sign You have contracted with suppliers to provide of something more severe such as potential goods and services. However, do you know fraud. It’s therefore vital that you identify when the supplier goes off-contract and erroneous transactions so you can recover these deliver something that doesn’t meet your overpayments as quickly as possible. Spend specifications? Spend analytics, integrated analytics will also help you to prevent duplicate with contract data, will inform you when items payments, preventing your organization from have been placed on invoices that go against leaking cash that could be used elsewhere. your supplier agreements. Supplier diversity Value of data Cash flow Establishing supply chain diversity isn’t just Lack of spend visibility negatively impacts good business sense, it’s often a government Spend data company profits because you can’t manage requirement. The challenge for most cash that you don’t see. Spend analytics organizations is not knowing the types of can help you improve cash flow by better suppliers; and this lack of visibility can often + understanding the cost of paying suppliers early. limit business growth. Spend analytics will tell Supplier product Further analysis such as high purchase order you how many of your suppliers are minority volumes under $100 could reveal an inefficient and women-owned businesses and through accounts payable process that requires your this knowledge you’ll be able to establish a = immediate attention. more robust sourcing strategy that will create Expand revenue significant value for your organization. opportunities through new channels

19 [email protected] www.rosslynanalytics.com Creating value from spend data

Key KEY Imp Spend data Spend data rove pro Data from other internalData departments from other internal departments outcome: understa cu ement nd if it rem cur anufact ’s sa en External data External data Pro r buy a m uring pla fe t d uild o nt in ec to b earthquake zone an isi Business outcome Business outcome P on ro s re at pa cu by su th other ym re co n ns rs data from internal de e m m : e io lie with partm nt en b e at p ata en s t in m l p t d ts to o in o u su en an s u g tc eg l em d/ u tc u r ca ur or p o sp o d o oc ex p m e n l pr ural disaster da te lie n ce a m e Nat ta rn r e: d n s o in al s p d a le fr b d a r a li u t m at n e t p r n o s a d v a e C le r s e w m h ru to t n it m t ec A o t it o e n s cc p e h c w r e lic o l u m b u l r o a e e u n e ro t g c c r p s ts a h n o cu . e p k n e e a r o .g lin surance quote a i e r L i p r e e In s n f l p , y o o p e l s id a g u r a n u b r i n io g le c s m m u r t g a o e a s d s s q t l in t a c x u y lis t h o e g I a f r E u r n e b e v d r li o p i a d p c t n u e a a s s t l c a d c P u n erty co o Prop sts r d a L o o d Em c r m n e e p u p e p l d s o r d y a r e d e is c e C i a e m e e l s r a t r m ly d P p a s t a u p C S d e e n e s u u r n a g e m y S p n a y o t r a r o e p s r o t o l o y t l s e o t i s u u l a t e t n C i n t r w n a a r t t e a o e a c s r p Combine t ) v s i n v s n e d o t p e d n e d

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20 [email protected] www.rosslynanalytics.com Conclusion

You need to have the right Organizations run on data. When tapped and refined into information, leadership, data strategy, you are able to do exciting and innovative things. technologies and business processes to prioritize and In a world where organizations are inundated with data from so many turn complex data into sources found inside and outside the office, the question is where to focus meaningfully information. efforts to deliver business value.

Rosslyn Analytics believe too many business and IT leaders are focused on big data projects, neglecting the large amounts of data already residing but untapped in your organization. This should be the priority. It’s why, for the first time, we have mapped out the value of data so you can deliver business value.

This unique research showcases a sampling of the insights that you can create by accessing, connecting and sharing data across your organization. But it is not going to happen overnight. It is a journey similar to that an athlete faces, to get into shape to win a race.

Value of data You need to have the right leadership, data strategy, technologies and Employee data business processes to prioritize and turn complex data into meaningful + information AND then to ensure it’s actually used to support decision-making. Employment predictions In the next section, we will discuss how big data is used practically, by executives in the following roles: procurement, supply chain, finance, product manager, marketing and human resources. Forecast= the cost of running company in competitive market

21 [email protected] www.rosslynanalytics.com Addendum 1.0 – Roles/Department

Value of data Five Ways Better Data Leads to Finance Better Financial Decisions Data is invaluable to finance – get it right Customer data A global data center service provider wants and revenue soars. Get it wrong… In 2014, to move into Turkey, because reports from Walgreens lost its CFO because he reportedly Gartner and Unisonius indicate that this region misforecast that the drugstore chain’s + has the fastest growing economy of the region pharmacy division would show $8.5 billion in Sales revenue where East meets West. Financial data (on sales for fiscal-year 2016. Three months later, the growth in the banking sector here) suggests the executive reduced the forecast by $1.1 this could become an international hub of billion. These mistakes are rare but they do = global trade. happen. Armed with the right data, better and Determine total cost of timelier decisions are possible. Finance can customer acquisition As part of its due diligence, the service provider and should use data in many ways, helping will consult regional economic data (from colleagues across the entire organization to say, the World Bank) and data evaluations on look into the past, present and future. This will how easy it is to do business in Turkey. (Even improve budgeting and forecasting capabilities business culture can be quantified.) The next and risk management capabilities. set of investigations will examine potential markets and customers, with data on previous patterns of spending.

Finally, more detailed data sources, which are co-dependent (such as revenue per service, cost per salesperson, and margins per service) will be examined, to see if the Turkish data center market is worth entering.

22 [email protected] www.rosslynanalytics.com Addendum 1.0 – Roles/Department

Value of data Procurement Supply Chain In the age of austerity, the cost of running The retail industry is under immense Spend data public services is a political hot potato. Whether pressure to tighten up its supply chain. Even savings are achievable without hurting front a one per cent saving can wipe millions off line services is a moot point. Data analytics can its running costs. In the UK grocery chains + only help shed light on this contentious area. like Aldi and Lidl surveyed the supply chain Employee names costs of stocking multiple brands of the same Analysis of the costs of procurement would product. Then they compared the costs of work on five levels. Firstly, the number of using one brand per product, the improvement = categories of products and services purchased in bargaining power by giving all their business Mitigate supplier- would need to be analyzed, to provide greater to one supplier. Analysis showed the costs employee collusion clarity when making purchasing decisions. of managing the supply chain dropped and fraud Clarity reduces errors. It’s often the case, in dramatically when the number of suppliers the public sector, that high staff turnover and was drastically cut back. long lead times for invoice payments lead to situations where suppliers are unwittingly paid The retailers than calculated how much several times for the same work. Analytical of these cost savings they could pass on tools can help eliminate these mistakes. to the consumer. As a result of this supply More detailed data on performance can lead to chain analysis, discounting retailers Aldi tighter management of the running of contracts and Lidl have made significant inroads into and enforce contract compliance, which saves a market previously dominated by the big the authority considerably from the risks four incumbents (Sainsbury’s, ASDA, Tesco of expensive lawsuits. A cross fertilization of and Waitrose). data sources can indicate areas where services could be shared, creating greater economies. Sales There are thousands of important stories Shedding more light on spending, and greater buried among the silos of sales data. The clarity exposes any malpractices because relationships between them are not always embezzlers have less option to hide. Using obvious or apparently logical. For example, these techniques the National Procurement the annual battle of wits between the retailer Service of Wales could save an estimated and the customer at Christmas means that £202 million. purchasing patterns are changing. Sales data shows that many canny customers are waiting until after Christmas to do the bulk of their shopping. Analysis of social media and shopping web sites (such as MoneySavingexpert.com) shows that shoppers are being urged to plan their purchases tactically. There is a significant demographic however, influenced by shopping deadlines, such as Black Friday, according to analysis. This data enabled many white goods retailers to have a highly successful pre-Christmas campaign.

23 [email protected] www.rosslynanalytics.com Addendum 1.0 – Roles/Department

Value of data Marketing Human Resources Most human beings display consistent Human resources are one of the hardest Product data patterns, according to shopping psychologists, variables to manage, and yet they make the and their analysis of customer data bears this biggest difference to outcomes. Each human out. History repeats itself, so historical patterns brain is infinitely more sophisticated than the + of customer behavior are a useful guideline most advanced computer that the combined Industry news to predicting future behavior. Purchase efforts of IBM and Google could produce. But histories, when cross referenced to reactions the human psyche is far more volatile than to competitor pricing, for example, could a machine and more prone to downtime = give retailers insight into how to protect their and defection. The studies of data related to Identify future skills markets. Tesco and Waitrose, for example, motivation (such as salary data, competitor gaps and prepare for analyze their customer data (as well as salaries and salary surveys) all give companies a battle for talent feedback from Twitter and Facebook) in a bid insight into employee wellbeing. to win back the customers they are losing to Aldi and Lidl. Customer perception of offers However, money is not the full story. Analysis (such as Buy one Get one free) is changing, of productivity and its relationship to and the retailers will be analyzing how satisfaction data is illuminating. The other customers react to these initiatives. motivations for work and factors for enjoyment can be measured by, say, social media analysis and data from companies that track Product Development social trends. Though the ‘soft skills’ and The amount of money a manufacturer invests psychological factors that affect human output in product development needs to be weighed are difficult to quantify, there is data available against the possible revenue, but this in turn to make educated guesses. This data might is affected by several other factors that are in a not be definitive, but it will help HR managers constant state of flux. In the green fuels market, and CEO to back up their ‘hunches’ and makes one company is facing a dilemma over how judgments more scientific. Human resources much money it should devote to developing are difficult to manage but big data analysis a biological, environmentally friendly form makes for better decision making. of aviation fuel.

The potential is huge but data will be analyzed to ask: which other companies are known to be involved in this? How close are they to launching? What is the price tipping point at which some airlines will go for a biofuel? How much more expensive would it be than normal aviation fuel? What sort of tax and carbon reduction savings would be available? Should the green fuel inventor ramp up production itself, or do the figures suggest it would be more cost effective and timely to sell its intellectual property (the secret of the manufacturing process) so that bigger companies, with a ready-made infrastructure, can sell the product under license.

These are all examples of product development data that analytics will shed light on.

24 [email protected] www.rosslynanalytics.com Addendum 2.0

Your internal data + Type of external data = Business Answer Customer + Income of customers = Better market to customers based on socio-economic information + Name of customers = Increase number of customers and prospects + Age = Know how much a customer spends and how much disposable income they have + Gender = Improve retention with better knowledge of customers profiles or personas + Occupancy = Reduce customer churn with better knowledge of customers profiles or personas + Location = Boost campaign effectiveness by targeting the right groups of people by geography + Family / dependents = Get a faster return on investment with more segmented / targeted marketing + Lifecycle phase = Increase number of high value customers by knowing who the high value customers are + Purchasing habits = Increase average revenue per customer by understanding buyer’s online behaviour Product + Competitors’ prices = Respond faster to a competitor’s aggressive pricing strategy + Industry prices = Benchmark your pricing against competitors + Pricing by location = Increase sales by localizing pricing based on market insight + Pricing by demographics = Accelerate customer acquisition by selecting appropriate regional partners + Testing = Improve operational efficiencies by incorporating emerging QA technologies and processes + Supplier costs = Reduce cost of developing products by expanding supplier base with innovative vendors + Customer thoughts about pricing = Predict consumer purchasing plans by monitoring lifestyles trends + Commodities pricing = Improve profit margins by leveraging fluctuations in commodity prices

Value of data Supply chain data + Government black lists

Prevent= fines by not trading with sanctioned entities

25 [email protected] www.rosslynanalytics.com About Rosslyn Analytics

Value of data Rosslyn Analytics (AIM: RDT), the leading global data technology company, Product data helps organizations create new business value from previously inaccessible data. We have developed exciting award-winning technologies designed + specifically for business users to easily access and turn complex data into Competitor price lists meaningful information via our RAPid Data Cloud Platform. No other platform, on premise or in the cloud, is such a game-changer, with a data technology stack that includes human-driven machine learning and NoSQL = technologies such as Hadoop, MongoDB and ElasticSearch. Respond faster to a competitor’s aggressive For more information including a demo, visit sales strategy www.rosslynanalytics.com or @RosslynBI.

26 [email protected] www.rosslynanalytics.com Value of data Customer data + Competitor customer wins = Hugh Cox Lance Mercereau Run an efficient, Founder, Chief Data Officer Chief Marketing Officer targeted sales program Hugh co-founded Rosslyn Analytics Ltd with Lance lives and breathes technology, always Charlie Clark. Hugh is a recognized expert in thinking of new and innovative ways of helping public and private sector organizations exploiting the latest such as cloud computing tackle business issues through technologies for the benefit of his customers. Lance started including cloud computing, data management his career - almost 20 years ago - at the height and analytics. of the San Francisco dot.com era, advising start-ups on business strategy, customer Hugh has authored and spoken extensively acquisition, alliance ecosystems, corporate on the subject of data analysis with particular affairs and brand management. focus on fraud prevention and detection, through the deployment of cloud-based Known for his aggressive “West Coast Offense” analytics platforms. approach to marketing, he subsequently moved to and worked in the United Kingdom Prior to establishing Rosslyn Analytics, and the emerging markets of Central and Hugh held senior positions with COO Eastern Europe where he successfully Investments (EMEA) and Citigroup Private established in-house marketing organizations Bank. He also worked for Perot Systems, and launched products and services for award- JP Morgan and Logica. winning companies such as Agilent, Dell, IBM, Intel and SAP, targeting enterprises, small After leaving the British Army, Hugh took a BSc and medium sized businesses (SMBs) and in Computer Science and an MBA from City consumers. After a year away as global head University Business School, London, UK. of marketing at a technology-focused business consultancy headquartered in London, Lance rejoined Rosslyn Analytics as its Chief Marketing Officer.

27 [email protected] www.rosslynanalytics.com