HELPING YOU DEFINE YOUR DATA STRATEGY
Data is a Strategic Asset
Businesses know their data is a strategic asset and they want to use it to make smarter decisions; but the problem is—it’s complicated. Often data is scattered in silos, stuck in departmental systems that don’t talk well with one another and quite often, the quality of the data is poor.
Businesses that apply data lifecycle management and ensure good handling of the information that they generate in their everyday operations and data strategy have several advantages that include:
- A good data protection infrastructure, which helps toward being compliant to the various data regulations that exist today
- Availability of clean, useful, precise data that is available to all users. This increases the agility and efficiency of operational processes and data analytics to support business decision making
BREAKDOWN
Building your data strategy
A vision for how a company will collect, store, manage, share and use data. It provides a data definition and articulates how data will enable business strategy and decision making. This sets the foundation for everything it does related to data.
Vision & Purpose
Incorporating a clear vision and purpose within your data strategy is vital. It provides a clear direction for how you intend to maximise the use of data.
Some essential principles to include in your data strategy are:
- Integrating Data and Eliminating Silos
- Streamlining Data Collection and Sharing
- Setting Clear Goals and Objectives for Data Management and Use
- Making Data More Actionable and Easily Shared
- Establishing Clear Processes for Data Management
- Establishing Guidelines for Data Analysis and Application
Policy & Controls
Establishing a policy that aligns with values is crucial. Taking control of your data gives you the means and visibility required to create a sound data policy framework to govern how data can, and cannot, be used. At the highest level, it’s all about finding alignment between what is possible with the data, what is good for business and also best for your customers.
While data policies are largely company-specific, there are a few baseline questions that every policy should answer:
- Who owns the data?
- What data is appropriate to leverage for business use?
- What data can we share?
- With whom can we share data?
Provides an Enterprise Framework that encourages teamwork to synthesise all the technical and business details surrounding an organisations data assets, across multiple data users in different departments.
Roles & Responsibilities
Probably the most important part of your Data Governance programme is to create the right roles and responsibilities. Who will lead your Data Governance programme, who will be the Data owners and Data Stewards and how will they understand what their objectives are?
Training & Communications
Providing your employees with training and ongoing communications around data is a vital part of your Data Governance programme. This will ultimately help you align your people behind the vision and help them understand their roles in your overall data strategy
Change Management
Most organisations have change management mechanisms for technology or software applications or websites. And yet, many organisations do not practice structured change management for data. One role of Data Governance is to set the scope of data-related change management and to oversee change management activities.
Privacy & Security
If you don’t have the right governance in place for your critical data assets then when it comes to applying privacy and security controls you’re unlikely to get that right. Regulations such as GDPR define what you can and can’t do with personal data and your Data Governance programme should support the implementation of this.
Data Governance Councils
A Data Governance council is the governing body for your data governance programme, raising awareness of its importance, approving enterprise data policies and standards, prioritising data related projects, and enabling ongoing support. Giving the right direction, the data governance council empowers all to create value from data assets while complying with security and privacy.
Escalation & Resolution
One of the most important jobs of a Data Governance programme is to help resolve data-related issues. These may be conflicting data definitions, data usage concerns, or problems with how data is sourced, how it is integrated, how it is protected, or a myriad of other issues. Having a clear process to log and resolve is key.
Data Quality
Data quality refers to the assessment of the information you have. The quality of data is defined by different factors, such as the accuracy, the completeness, the consistency, or the timeliness. That quality is necessary to fulfil the needs of an organisation in terms of operations, planning and decision-making.
Access & Ownership
Are you clear about who can access data and who owns specific data within your company. Your Data Governance programme should define controls around the ownership and access of data. In particular, personal data needs to have strict controls to ensure compliance with regulations such as GDPR
Building a data strategy that drives value from data means that you have to look at all aspects of your business. Your People and Culture, your Processes & Operating Model and your Technology.
People & Culture
To be successful in driving value from your data, you need to make sure you bring your employees on the journey. Are they clear about your vision, do they understand the role they will play. Are you building their skills to enable a data driven culture.
Process & Operating Model
There are many ways to build your Data and Analytics function. Will you go with a centralised, de-centralised or hybrid function. Are you clear on the pros and cons of each and which one will drive more value for your business.
Technology
Having a strong view of the technology you require to exploit the value of the data you collect is key. There are thousands of options available today, but be clear on understanding what you need rather than being caught in the “hype cycle” and making mistakes that don’t deliver what you need long term
Data management is best seen as an IT program, whose goal is to organise and control your data resources so that it is accessible, reliable, and timely whenever users call on it.
Data Architecture
Businesses that start with a vision of data as a shared asset ultimately outperform their competition. Provide the right architecture that allows data to be collected, stored and used appropriately. Don’t make it difficult for data to flow throughout your business.
Data Lineage / Traceability
Data lineage is the process of understanding, documenting and visualising this data as it goes from origination to consumption. It is the process of tracking data upstream from its end point to ensure the data is accurate and consistent. It covers looking at the origin to destination path, both forward and backwards, and at any point along the path.
Data Standards
A set of data standards is vital for businesses looking to drive value and insight from data. Not collecting and storing data in a required format will drive ambiguity and errors. As a result, your data analysis will never quite be right!
Master Data Management
If your business has multiple on-boarding applications or customer databases, then it is likely that you will need to consider Master Data Management (MDM). MDM is the process of linking all the critical business data of an enterprise to a single point of reference. It reduces errors and makes business processes less redundant.
Data Catalog / Inventory
A data catalog is a data and metadata management tool companies use to inventory and organise the data within their systems. Implemented well, your people will understand the data within your systems. They will believe and rely on the data’s accuracy when answering business questions and will be able to deliver analytics at speed.
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