The Truth about Data Truth: SSoT vs MVoT

Business Intelligence, data visualization

In our last article we looked at the differences between data and information – data being the raw binary code that businesses mine, and information being that very same data but ‘endowed with relevance and purpose’. Raw sales data by itself, for example, can be meaningless. But put it in an historical context by comparing it with preceding months, and you’ve suddenly got actionable information. We discussed the subsequent differences in the architectures designed to manage both data and information, and how aiming for maximum control within these architectures might ensure accuracy and compliance, but can also limit your options when it comes to business growth.

This control mainly stems from the sources of your data and information – it follows that if you control the sources, you control the data. Controlling data sources is great news for those within your business who are interested in compliance and regulation, as this data can be easily managed and manicured. But being in total control of the data denies you a world of valuable insights, inhibiting many opportunities for growth. The answer, for most businesses, is to find a happy middle ground between control and flexibility when it comes to data sources. And as the Harvard Business Review recently outlined in this extensive article, this is best summed up by looking at the two types of sources available to your business – Single Source of Truth (SSoT) or Multiple Versions of Truth (MVoT).


Single Source vs Multiple Versions

So what are the differences between these two data types?

Single Source of Truth (SSoT) data, as HBR defines it, relies on one unchallengeable source within your own organization to deliver all the crucial data needed to run your business. Things like customer details, supplier details and product information should come from a SSoT, which provides an excellent level of control, perfect for those who are concerned with regulation and compliance. This data is reliable, and can be used by departments across the business – it isn’t specific to any one part. Not having a SSoT can be chaotic for any business. If you have multiple sources of customer data, for example, your accounts department could find itself dealing with AAA Corp while sales might list the customer as AAA Inc, leading to confusion, mistakes, and a lack of understanding about the organization’s relationship with said customer.

When we talk about Multiple Versions of Truth (MVoT) we’re not talking about alternative facts, HBR tells us that we’re simply talking about turning this raw SSoT data into information. Each department of the business will take this SSoT data and imbue it with relevance and purpose by putting it in some form of context – comparing one month’s sales figures to others, as per the example above – which will inevitably alter it, turning it into its own distinct (and hopefully well controlled) version of truth. This version of truth is specific to the department, and will be able to offer responses that align with their unique requirements.


Real World Applications of SSoT and MVoT

Let’s use an example. Say that you’re an organization who supplies both Samsung and Ford. In an SSoT these companies might be difficult to distinguish, or simply be delineated by placing a label of ‘Consumer Electronics’ on Samsung and ‘Automotive’ on Ford. But depending on the sort of business that you conduct with these companies, such arbitrary labels may be of little use in distinguishing how you deal with them. Sales departments who are looking to grow the relationship need a deeper understanding of how they work with their clients than SSoT can provide, and for the purpose of competitive analysis will need to turn this data into actionable information, using a variety of datasets to put it in a greater context and creating MVoT in the process.

Consider too the way that an organization’s marketing and accounts departments might produce reports on marketing spend. The marketing department, focusing on the effectiveness of its campaigns, reports spending figures collected just after ads have aired. The accounts department, focusing instead on the organization’s cash flow, reports spending figures as invoices are paid. The figures will be different, but neither is incorrect. They’re just altered to fit the requirements of the separate departments. In short, SSoT works best at the data level, where the pure, raw data should be clinically managed and harvested. But once an area of an organization needs to set that data in context – to transform it into information – MVoT should come into play to create a more practical version of the truth.


The Need for a Combined SSoT/MVoT Strategy

The pure use of SSoT data, while allowing a business to stay in perfect control, does not inspire growth. It inhibits it, in fact. By not allowing different departments to interpret the data in the ways that they require, you are missing out on identifying a wealth of growth opportunities, both within your current customer base and in new markets. While an organization’s finance and legal departments appreciate the control and stability of the SSoT approach, those charged with moving the business forward will find themselves stymied.But moving too hastily into the MVoT space can open your business up to serious hazards. MVoT will result in variety of seemingly contradictory information within your organization, and ensuring that you have systems and procedures in place to make sense of this confusion is vital. This is usually done via an automated synchronization program which merges SSoT and MVoT data at the end of every business day, identifying data integrity issues and solving those that it can while highlighting those that it can’t. So it’s vital that Single Sources of Truth are carefully collated and held as gospel, but that Multiple Versions of Truth are allowed to diverge from this single source from department to department, albeit in carefully controlled ways.

Unfortunately what may seem simple in theory is anything but. A firm set of data controls, good governance, and purpose-built technology are all required in order for a combined SSoT/MVoT strategy to work. A proactive C-Suite is also vital – indifference from above will ensure that any SSoT/MVoT strategy will fail before lift-off. The approach from the C-Suite is exactly what we’ll be tackling next. Does such an important job as controlling your data strategy necessitate a purpose-built position? Would your organization benefit from the employment of a Chief Data Officer?

We’ll be weighing up these questions and more in our next article - Should You Invest in a CDO for Your Data Strategy?