While data capture and usage on the scale of Google, Amazon and Facebook is beyond most businesses, building a low-cost data-driven organisation is easier than you think, according to Carl Davis, founder of technology consultancy Downswood.
Google, Amazon and Facebook, three of the most highly valued companies in the world, are masters of data capture and usage. Their ability to use technology to harness the power of data and understand customer behaviour is second to none.
While data capture and usage on such a scale is beyond most businesses, building a low-cost data-driven organisation is easier than you think. Implementing a data strategy and looking at how you can start to treat data as an asset will help ensure your business is smarter than its competitors and more flexible to cope with change. Companies that don’t change run the risk of being left behind.
What becoming data driven looks like in practice
Let’s take a simple example. First, you assign members of staff to become Data Stewards. As the name suggests, a Data Steward is responsible for maintaining data control and governance on a daily basis.
Dun & Bradstreet define a Data Steward as someone with the responsibility for the data definitions, data quality and processes within an area of competence. This is not necessarily a full-time role and members of staff could take it on as an additional responsibility.
Once the Data Stewards are in place, it is a good idea to invest in their data governance training; although this isn’t essential it will definitely benefit them and your business.
The new Data Stewards will be responsible for cataloguing all the available ‘data assets’ and understanding data workflows.
Example data assets include a credit score, customer email address, asset performance rating, customer liquidity ratio, customer turnover and customer fleet size. From a technical perspective, a “data asset” can sometimes be described as a “data point”; this can be defined as a discrete unit of information or a fact.
A data asset will have the following characteristics:
● A description and classification, as well as a business purpose and value
● A quality score – an internal calculation on how accurate, usable, consistent, unique and trusted the data asset may be
● Governance, security, compliance and access rules
● A collection process
● Externally or internally produced
● Possibly have a relationship or link to other data assets
● Part of a business glossary, data catalogue, data dictionary or internal policy
● Belongs to a business domain or an internal department
● Belongs to an owner and/or subject matter expert.
Define and improve your data assets
Start by listing and defining your data assets. If resources are limited, you can do this in Microsoft Excel, but this can be achieved more effectively through specialist data governance software such as Collibra, Erwin or Informatica. The benefits of using these tools is that you can automate data discovery by pulling in information directly from internal databases, spreadsheets and other sources of data assets. This means that future changes made to internal databases can be automatically refreshed to your data asset catalogue, which simplifies the process of initially documenting data assets and keeping an up-to-date record of the data that is available internally.
Once the data classification is complete and shared across the business, you need to turn to reporting and analytics to get the real benefits from your investment. Analytics and reporting transform data from being simply a perceived fact into becoming an asset. Depending on the scale of data assets that are available, you should consider using specialist tools (mentioned above) to publish assets across the organisation. Finally, you can monitor the performance of data assets that are key business drivers.
Examples of business driver data assets are:
● Lead-to-conversion ratio
● Customer complaint %
● Net Promoter Score
● Average customer feedback score
● Average lend/quote decision time
● Average customer credit score
● Default rate
● Average lend/lease value per transaction
● Number of transactions per month.
A data-driven organisation will recognise that an improvement in any of the data assets above will improve the bottom line.
Eight reasons why data is an asset
1. Provides an insight into customer behaviour or future need
2. Increases consistency and confidence in decision making for credit and underwriting teams
3. Creates new products or methods of pricing risk
4. Decreases the risk of regulatory fines
5. Improves data security and governance
6. Designates accountability for data assets and information quality
7. Enables better data-driven decisions
8. Improves marketing and origination
Four steps required to become data-driven
2. Define your business objectives and impact
Strategy: Ensure practical strategic alignment with business objectives.
3. Define and document data assets
Low cost tools: Microsoft Excel with data asset catalogues and policy documents in Microsoft Word.
High tech tools: Data governance tools such as Collibra or Informatica.
Wherever you are on the journey to becoming more data driven as an organisation, taking steps to improve your data insight, management and governance, however small, will turn the data you hold into a more valuable asset and enable you to compete more effectively in today’s data-driven economy.
* Downswood was founded by Carl Davis, a former chief technology officer, who has led many award-winning projects in the financial services sector. Projects include the digitisation of asset finance and invoice discounting and delivering data-driven automation. Davis holds an MBA degree from the University of Cambridge. Downswood helps clients realise their digital potential through strategic technology consultancy, technology procurement, systems integration and software development.