DATA STRATEGY. Sally Carey White Witch

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1 DATA STRATEGY Sally Carey White Witch sally.carey@datamine.com CREATED BY DATAMINE REINZ - DATAMINE MODELLING CAPABILITY 1 Datamine 2018 All Rights Reserved

2 What are the components to a comprehensive data strategy? This whitepaper is written for the non-technical business user and details how to approach the initial development of a data strategy to support marketing plans and activities. We ll define the qualitative and quantitative components of a data strategy to support marketing planning, as well as describe ways to implement the strategy in the day-to-day. The generic approach described is relevant across industry sectors, to organisations of all sizes, both product and service. INTRODUCTION This paper explains the importance of data management, the issues facing those involved and how to address them. It isn t based on a particular propriety system or software, but instead is businessfocused, aiming to provide the knowledge required to successfully create and implement a data strategy before moving marketing data to a datamart. Marketers require access to the information they need and confidence that it s based on the correct underlying data, so implementing a datamart is a natural step when trying to achieve better insight into their organisation s data. Before this step, though, a data strategy must be set in place a process that is too important to address on a piecemeal basis. Often the focus on data comes as a result of an issue or challenge, such as a database performance problem. Instead we suggest that marketers work from their big picture, defining what is required rather than scrambling to find data as the need arises. Does your organisation need a data strategy? Having a strategy to capitalise on your data is relevant to organisations of all sizes. The reason to have a data strategy is simply to capitalise on the asset that is your data. It can be used strategically to underpin marketing planning and tactically for many marketing activities. We ll go into further depth about how data is an asset later, under the heading, The Benefits to Marketing. CREATED BY DATAMINE DATA STRATEGY 2

3 Unsure what data is available Difficulty accessing data Data quality issues A variety of problems are evident in the absence of a data strategy Non-existent or poorly understood data standards Unclear responsibilities Importance of data not appreciated within the organisation Increasing dissatisfaction with IT The implementation of a sound data strategy results in the development of a datamart with less risk and a higher success rate. The components of a data strategy A data strategy has two overarching sections. In the first, your organisation needs to outline its goals and objectives for investing in analytics, describing how you plan on leveraging data and what kind of opportunities it could provide. This section will require input from different departments throughout the business, as well as a firm approval from management it is the qualitative foundation that your business will be able to revisit over time as you build your analytics capabilities. In this section, you and the management team/stakeholders will need to discuss questions such as: Why are we investing in analytics? What do we want to achieve from better insight into our data? What are the foundational projects we first want to focus on? What KPIs will we set for our analytics initiatives? Where do we see our analytics department in a year s time? What will we need to do to get there? The next section of the data strategy will look at the infrastructure your organisation will need to put in place in order to facilitate the goals outlined in the first section. CREATED BY DATAMINE DATA STRATEGY 3

4 The primary components of this section are as follows: data content quality performance roles & responsibilities ownership integration with legacy or operational systems data migration security privacy software and licencing measurement communicating the data strategy internally Let s look at each of those components individually. Data content Your data strategy will review the information available across the organisation (and beyond) to define which data will be incorporated. Where to begin? Start with the basics and add on from there. This includes data like customer information e.g. names, addresses, telephone numbers, address, date of birth etc. and purchase history e.g. product, date, amount, payment method, channel. If a rewards or loyalty programme exists, then this is also key information to incorporate into the datamart. Examples of rewards data are join date, points balance and rewards redemption history. Prospect and leads generated from another source of data are also important and may be gathered from a web-site or mobile device. The next tier of information is communication history, including ingoing and outgoing communications across all channels. Unstructured data, such as call centre notes or enquiries, can be added later. Your own organisation s data is the most valuable data. Some other sources that can be used to augment your own data are QVNZ for property and rural information, Census data for demographics, weather information (particularly useful for retail), media data etc. Data quality The data quality section defines arrangements for on-going data quality review and stipulates how the data will be audited. For example, a standard for address information in CREATED BY DATAMINE DATA STRATEGY 4

5 New Zealand is called a Statement of Accuracy. The term for a Statement of Accuracy is one year, therefore provision needs to be made to review this annually. This section of the strategy will also contain requirements for the currency of data, e.g. will updates be required weekly, monthly etc.? The timeliness will depend on the nature of your industry and how the data repository will be used the more up to date, the greater the cost typically, therefore there needs to be a reason for requiring real time updates. This section should also address whether the cleaning effort made for the data repository is going to be fed back to the originating systems, which can be based on a cost/benefit approach. Decisions will need to be made regarding prioritising the cleaning effort, how to manage missing data and business rules that can be implemented to ensure on-going data quality. It s helpful to define who is responsible for data quality - if it is everyone s responsibility, it often turns into no-one s responsibility! Performance This section defines the performance requirements, covering both data and people. From a data perspective, it s important to estimate the capacity requirements and anticipated growth for the data repository. Reporting should be available for computer process intensive routines that require monitoring. From a people perspective, outline the response requirements for the roles involved, such as systems administrations and analyst availability. Roles & responsibilities There are a number of roles required for the execution of the data strategy. These include Database Administrator, Developers, Analysts, Modellers, Business Analysts and a Project Manager. Ownership This will define the person responsible for key aspects of the data strategy and datamart. There may be different people responsible for the initial build and the on-going maintenance. System integration Determine how the data repository will interface with existing systems. There needs to be a flow of data from the existing systems to the data repository, and it may also be useful to plan a flow of data from the datamart to the existing systems (for example, import customer segment to the call centre data display). CREATED BY DATAMINE DATA STRATEGY 5

6 Migration The initial set up or populating of the data repository requires consideration and will cover how far back in history data will be loaded. This is an area where assumptions are often made and expectations not met, so make sure to spend sufficient time on this step. Security Define the security arrangement for the datamart it is usual to regularly back up (daily) and for a recovery process to be implemented and tested. The frequency of back-ups depends on how frequently the data is updated or refreshed. Access to the data can be restricted to protect your asset. Privacy Privacy laws exist in most countries to protect individuals (for example, the Marketing Association in New Zealand has guidelines and provides support to its members regarding privacy compliance). These laws do not usually extend to information held about individuals within companies. Software and licencing It s also crucial to consider the technical platform and the licensing costs, which can often vary by the number of seats in use or the amount of data being processed. Note that there has been a spike in free, open source technologies with the growth of the internet. Measurement This section defines what will be measured and what measures need to be met. Start by considering the outcomes you need to achieve and what measures can be put in place to achieve these outcomes. Measurement can cover roles (e.g. systems administration to keep the data repository available during business hours) or usage (who is using the data repository and how much use it is getting?) among other things. Communicating the strategy Once the strategy document is complete it needs to be communicated to management and the users. People need to understand the purpose behind the repository and its functionality so that expectations are managed. This communication needs to happen on an on-going basis as new people join the organisation. CREATED BY DATAMINE DATA STRATEGY 6

7 The benefits to marketing The benefits of a well-implemented data strategy to marketing are many, and they have far-reaching business benefits. Here are some of the notable benefits: Productivity It is common for analysts to spend 60-80% of their time locating and preparing data for analysis, leaving only 20-40% left over to perform the analysis. With a data strategy and datamart, these numbers can be reversed, allowing analysts to spend as little as 20% of their time gathering and preparing data for analysis. Cost containment The datamart can help to control costs in a number of areas, making it a good area to obtain some short-term benefits. Costs can be reduced by minimizing inventory, minimizing promotional mailers, and using more cost-effective channels to deliver services. Revenue growth Improved marketing can produce more revenue per customer resulting from increased spend and a greater share of the customer s wallet. Selling higher margin products, focusing on the more profitable customers, and turning unprofitable customers into profitable ones will all serve to enhance revenue. Conversion rates Achieving a better understanding of the customers, as well as targeting prospects with the right products, channels and incentives, can dramatically improve the conversion of prospects to customers. Retention By knowing which customers are likely to leave, and knowing their relative profitability, you can take appropriate action to minimize customer churn. I ve created a data strategy now what? The information above should give you a good idea of the components that go into creating a comprehensive data strategy. It s a high-level view of what your analytics activities need to be in order to enable smarter marketing and better data management through a datamart. Challenges can arise when organisations have created a data strategy but aren t sure where to begin implementing the practices on a day-to-day scale. In such cases, it s important to supplement your data strategy with an analytics roadmap. An analytics roadmap is a framework for the implementation of the data strategy a plan that allows you to evaluate the potential of each strategic initiative. Such a framework is integral to the successful CREATED BY DATAMINE DATA STRATEGY 7

8 application of a data strategy, as it can otherwise be daunting to translate such overarching concepts into actionable activities. To give an example, the data strategy might outline what kind of data you want to include in the datamart (e.g. your customer data, Census data and banking data) and your analytics roadmap will determine where you will get that data, who will clean/organise it, where it will be kept etc. It helps turn big projects into smaller, more achievable steps for you to take. If you re struggling to implement your data strategy, it might make sense to run it by an expert and work with them to create an analytics roadmap they will have fresh eyes and an objective opinion on your strategy, as well as the expertise necessary to helping you create a plan of action moving forward. SUMMARY Gaining value from your data and turning it into a strategy involves: Knowing what data to collect and having processes to maintain that data Consistent security implementation Understanding, defining and assigning ownership Categorising data Developing consistent terminology And the key criteria for success for your data repository are: Quality data Interface with legacy and transactional data Solid infrastructure (people, skills and tools) Rapid implementation to get some quick success Once your data strategy has been outlined, work with an expert to create an analytics roadmap this will give you the day-to-day direction necessary to implementing the goals and tactics from the data strategy. CREATED BY DATAMINE DATA STRATEGY 8

9 About the author Sally Carey is a director of Datamine and has over 20 years experience consulting on data analytics solutions across a range of industry sectors. Sally specializes in delivering clarity from the complexity of big data advising organizations on a host of predictive analytics disciplines - including quantitative decision making, loyalty programmes, organisational change and marketing strategy. Datamine experience With over two decades experience helping organisations unlock the value in their data, the team at Datamine have helped numerous clients outline their vision for analytics through a data strategy. This is done in part by first auditing data (cleaning, organising and reviewing it) and then planning (defining goals, outcomes and changes that will need to occur along the way). Beyond data strategies, Datamine has ample experience in the creation of analytics roadmaps helping businesses put their data strategies into action. Contact us today to learn more. Case study CREATED BY DATAMINE DATA STRATEGY 9

10 Testimonials Westpac Cards was at a point where we needed to leverage our data to make key decisions about our future marketing investments and strategic priorities. They provided us with fantastic quality outputs, were always professional and friendly, and gave us insights that enabled us to make some key strategic decisions very quickly and with confidence that we were going down the right track. I have already recommended Datamine to colleagues in other fields and know that they have been equally pleased with the results." Head of Call Centres at Westpac "Datamine provide answers to help us make better, more informed, decisions. Personally, I like to have all the facts, and, through our work with Datamine over many years, we have seen things that have led us to make different decisions than we would if we d just gone with our gut feeling. Datamine provide us with evidence of what is actually happening in our business. This can be different to what we might believe and, at the end of the day, helps us to be more effective." New World Brand Champion, Foodstuffs Auckland Ltd With over 20 years experience, Datamine is a leading analytics consultancy dedicated to enabling businesses to implement smart, data-driven decisions. Using our 350+ different solution types, including segmentation, profiling, churn detection and modelling, operational excellence, strategic direction and performance improvement, we deliver repeatable success across a range of industry sectors, such as banking, telecommunications, energy, retail, insurance, travel, FMCG, government, and healthcare. Datamine is all about connecting and empowering people to benefit from data analytics every day. With a focus on collaboration, innovation and pragmatic excellence, we re passionate about giving organisations the knowledge they need to unlock the value in their data. Contact us today Datamine Limited Auckland Sydney Melbourne DATAMINE ( ) contactus@datamine.com CREATED BY DATAMINE DATA STRATEGY 10