What data is
90% of today’s data didn’t exist before 2019. There’s more now than ever before, but what exactly is data? Data is a fact or entity such as names and numbers. It is an imprint of an action. It’s someone filling in their details to an online registration form before making a purchase. It’s an interaction with you on social media. It’s someone sending a contract emailed to your finance team that requires action. It’s known or assumed facts.
White paper – What your data isn’t telling you
What data you should capture
There isn’t a set list of data you should capture. Defining what data you capture, and how you then manage it, should be defined as part of setting out your data management strategy. A topic we come on to later. But for now, some of the more business fundamental types of data include:
Data sets so large and complex that traditional software can’t deal with it efficiently. A combination of structured, semi-structured and unstructured data it can be mined for information and used in machine learning and predictive modelling.
Transaction data is data describing an event. Transaction data always has a time dimension, a numerical value and refers to one or more objects. It includes things like sales orders, invoices, shipping documents and so on.
A single source of common data used across multiple processes. The two most common types of master data is product information: colour, weight, price, size and so on, and customer data: email address, name, age, date of birth, and so on.
Meta data provides information about other data, such as how long it is valid for and where, when and how it was created. This data is key in understanding the state and quality of your data before commencing any data management programme.
Machine data is the data created by control and operational systems, IoT sensors, and your industrial network. If made accessible and usable, machine data can help you identify threats and use machine learning to predict issues before they arise.
What is data management?
“If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” ― Jim Barksdale
Compiled and translated, data becomes insight an organisation can use to direct decision-making actions with a greater degree of certainty and successful outcome. Data management is essentially the practice of collecting, organising, protecting, and storing data so it can be analysed. As your organisation creates and consumes an increasing amount of data, data management becomes essential for making sense of operations.
The benefits of good data management
Implementing good data management practices precede analysis and analytics. It’s the crucial first step to effective data analysis at scale. Until you are feeding your analytics tools with good quality data, the insight presented will not be accurate and may lead decision making astray. This said, managed well, data leads to important insights that add value to your customers and improves your bottom line.
For example, data collected on customer purchase history enables you to create more personalised offers and experiences. This leads to customers buying more often and spending more when they do. Analysing shipping data allows you to select the fastest and most economical routes when ordering or moving goods.
The process of improving data management also delivers advantages in efficiency and cost reduction. For example, cutting the number of data silos brings down the cost of managing each disparate system. It also makes access and management of data easier to control.
With effective data management, people across your organisation can find and access trusted data for their queries. Some benefits of an effective data management approach include:
With better visibility of your data, you can make decisions based on fact. With the insight data provides, you can introduce new products, services, and initiatives with greater certainty of success.
Visibility of data across the business also encourages others to take ownership and use it to improve the outcomes of their own activities and engagements.
Connecting data silos makes it easier for the business to view customers, products, transactions, and so on, as a connected entity. This also reduces the cost and time of managing multiple silos.
From data preparation to cataloguing, search, and governance, people can now quickly find the information they need for analysis.
Why your analytics is probably lying to you
Used well, analytics software will spot trends in your data, offer direction, and support business strategy. But it has one major flaw: it is only as good as the data that feeds it. If the quality of data is compromised, then whatever your analytics shows is a lie, because it tells only part of the story. And that itself may be inaccurate. This short podcast discusses this challenge and how you can solve it.
The data management challenge
Data is so broad, so vast, and so wide reaching, its impact is felt on every employee and every customer in your business. Every touchpoint, and from every activity, yet more data is created. It’s the responsibility of all to maintain its upkeep. And this itself creates perhaps the biggest challenge when it comes to improving how data is managed in your business: ownership.
Data silos = data duplication
Data is captured and stored in independent silos, for example, one business unit uses one ERP, and another unit uses something entirely different. Similarly, customer information captured from eCommerce may be stored in one CRM, but the contact information marketing and sales use to reach out to customers resides in a different CRM. The same customer is duplicated across both.
No owner = lack of purpose
Do you know why you capture the data you do? Many businesses don’t. It’s this lack of purpose that is at the root of data management problems. Data management is the responsibility of everyone in the business, and until this mantra is adopted as part of its culture, you will continue ingesting data in a structureless way, without aligning its purpose with that of the wider business objective.
Not fit for purpose = data for data sake
Capturing data just because it’s there, and in the belief it may, at some point, yield value your business can extract, is the ‘strategy’ for many. To ensure you don’t flood your business with data it doesn’t need, and to prevent the cost this ensues, ensure you align the data you capture to the business strategy. Identify the data you need to help move the business towards its objective.
Manual input = poor data quality
You will never completely get away from manual data entry. There will always be a need. It’s simply a fact of business operation. From manual entries into sales ledgers to keying the name of prospects into your CRM. But the more manual data entry there is, the more mistakes, and the lower quality of data, you will have. And how big this problem is in your business doesn’t bear thinking about.
What are the signs you have a data problem?
Sending customers the wrong information about something they’ve bought. Providing an offer that doesn’t relate to a past purchase. Displaying inaccurate product information. Having multiple versions of the same customer stored across siloed finance systems. These are all examples your data is not in the shape it needs to be to provide value.
How to improve data management
There is no one tool that solves the data management challenge. In fact, managing data in such a ways that it delivers value across the business relies on a combination of things:
Process and culture
Data is an organisation asset. It touches every part of a business and, well managed, offers value to all. It is therefore the responsibility of each employee to ensure it is well cared for. The easiest way to increase ownership is to create a data driven culture. A data driven culture ensures ownership and helps maintain buy-in and support from the top of the business right through to the bottom.
People and owners
Let departmental data experts take ownership of teaching and helping others in the business use data the right way to increase data literacy. Part of your strategy to increase awareness of the value of data, and the successful deployment of data projects, is to find business stakeholders who can act as data ambassadors and support the spread of your data value message.
Governance and management
Once you have a grasp of the data you want to capture and manage – by identifying the business-oriented purpose it should serve – instilling a data governance framework allows you to define the boundaries and processes needed to manage and monitor it. As people in the business interact with data, a governance framework will guide their use of it so it continues to serve the original purpose.
Tools and integration
Now begins the process of choosing the platform and tools you’ll need to enable the business to capture, manage, analyse and get value from your data. Start by building a picture of your nirvana data state, then identify technology gaps against it i.e. do you want to be able to link data across siloed business units, or pull into a central place of management? Do you need tools to identify and cleanse issues in your data? Are you able to measure and manage data quality?
How data can improve your customer’s digital journey
There’s a lot that’s been made of the importance of the digital journey when it comes to the buying experience, but why is it so important and what role does data play in helping define the journey? But most importantly, how will you, your business, and your customers benefit by creating a connected digital experience? This short podcast explains what you need to do.
Having a clear data strategy is essential in today’s digital world. Only by developing a clear roadmap can the necessary attention be given to your data – the untapped asset in your organisation. A data strategy helps unlock the benefits from the many opportunities of using data to deliver value to your organisation.
HSO helps its customers define and implement their data strategy. During the definition phase of our engagements we:
- Audit your data sets – recognise that some data is better/more important than others
- Establish the right level of governance
- Review your data related processes
- Assess the need for improved technology solutions
- Identify the help needed for your people to improve their use of data
Working with your teams we define the appropriate data strategy roadmap for your organisation and help ensure a focus on the value your data strategy will bring to all stakeholders.
Business Intelligence & Analytics Maturity Assessment
HSO work with our customers to support their understanding of their BI&A Maturity. Through a structured process we capture a detailed understanding of not just your current areas of strength, but also gaps in your current BI&A related activities. Once assessed, areas of future improvement are identified and plans to move along the BI&A maturity curve are defined.
Microsoft data platform
One of the building blocks of digital transformation is a data and analytics platform that harnesses data’s power to reveal patterns and make predictions. Being able to understand and tap into these predictions helps fuel digital transformation.
The power of Microsoft’s data and analytics platform is that it allows you to gather, store, and process data of all types and sizes from any data source to act as the fuel for digital transformation.
Deeper data understanding unlocks valuable insights, making it easier to identify trends and risks that help you ship on time, provide a quality product for our customers, cut down on business costs, optimise internal operations, whatever your business goals are.
As a Microsoft Gold Partner, HSO’ experience helps customers achieve all the results they need from a modern data platform.
Fast and agile
Work with a flexible data platform that gives you a consistent experience across your business enabling you to get new products to market faster.
The Microsoft data platform introduces Artificial Intelligence providing deeper knowledge about your business and customers. Machine Learning also provide faster predictions and better security.
Leverage the insight from data to build apps quickly and then deploy anywhere, opening new avenues to productivity and revenue.
HSO DNA Accelerator Capabilities
Gather: Consolidate data from multiple source systems to produce a single 360-degree view.
Profile: Link entities to enrich information and present a more detailed picture.
Cleanse: Generate accurate and validated data used easily in other systems.
Manage: Streamline and automate business processes around data to fuel decision making and support data governance.
Share: Improve collaboration and support growth by ensuring access to consistent and accurate data.
Govern: Know where your data is, where it has come from, and what it’s being used for – making it easier to support the GDPR.