An executive committee met to address pressing problems confronting their rapidly expanding company, but it quickly became apparent that they did not speak the same language. It didn’t matter whether they understood what was being said since the basis of their conversation was flawed.
The starting points that shaped how each CEO saw the company’s current problems and objectives differed greatly. Instead of coming up with a plan on how to deal with the company’s growth problems, each CEO exited the meeting wondering whose numbers were accurate.
Instead of being empowered by data to make better decisions, they were held hostage by it. By establishing data silos, businesses are generating a “Tower of Babel” phenomenon, where various teams are unable to work together to develop the company because they don’t speak the same data language.
There are still companies with numerous data silos and conflicting interpretations of the truth despite the obvious dysfunction caused by fragmented perspectives of company performance. Marketing departments, on average, make use of over a dozen marketing platforms. With so many digital marketing tools at their disposal, marketing teams may easily surpass this benchmark. It may be difficult for marketers to determine which statistics to rely on when various tools—even comparable systems such as Google Analytics and Adobe Analytics—are spewing out different information.
Similar-sounding metrics may measure very different things. When and how data is gathered, and the settings and processing used within the various tools may make a big impact. Marketing teams and businesses may easily waste time and resources on initiatives that don’t provide results if there isn’t a single version of the truth.
What exactly do we mean when we talk about the “one truth”?
In analytics and business intelligence discussions, the phrases “single version of the truth” and “single source of truth” are often used interchangeably. However, in terms of data management, they complement and connect to each other, but they imply different things. We will examine the distinctions between the two words and provide the following definitions:
Data storage concept that requires a specific piece of information to come from just one place: the single source of truth.
There really should be a single version of the truth that everyone in the business believes is the actual, trustworthy figure for certain operational data.
Instead of focusing on managing fragmented data across several systems, a single source of truth aims to provide relevant data so that business leaders can easily understand company performance. Instead of combining data from many sources, a single version like a CRM features concentrates on consolidating and harmonising reporting and analytics into one place. In other words, success in achieving these two goals may converge or fail to do so. It’s not necessary to have a single source of truth to create a single version of the truth. Your technical staff may face major challenges when it comes to consolidating all of your data into one place. When you and your team come to an agreement on a single set of important KPIs, it will be much simpler and less time-consuming to put them into practice.
What is the significance of this?
You cannot afford to have alternative facts in your company, unlike in certain political circles where they seem acceptable. If you want to operate your company successfully and efficiently, you must get rid of them. Confusion, paralysis, and poor decisions may all result from conflicting interpretations of the truth. Data that is inconsistent or conflicting makes it difficult for a company to have faith in its present performance or future forecasts.
Most B2B businesses, for example, place emphasis on generating leads in order to increase revenue. A “lead” may imply various things depending on the marketing system or platform you’re using. When someone fills out an online form, it counts as a lead in your digital analytics tool. All of the contacts you established at a trade show will appear as leads in your CRM system. Your marketing automation system will remove filters and duplicates to produce a “qualified” lead. It is possible that your sales staff may only consider specific marketing leads as genuine sales prospects.
Which variant should you pick if you want to optimise your company for “leads”? There may be severe repercussions if teams are not aligned throughout the company, as they will wind up pushing in various directions—many of which will be incorrect.
How can you get to a consensus on the only true account of events?
When one version of the truth is introduced, alignment and buy-in become more important than accuracy. Your main stakeholders must agree on the key metrics that will be used to track company success if you want a single version of the truth. You’ll run across data quality problems and data gaps as you move through the alignment process.
We suggest beginning with a problem where you are aware of the limitations of the data, but you are also committed to going ahead with the solution despite those limitations. Perfect numbers are the foe of excellent ones in this situation. Instead of waiting (and waiting) for flawless figures, it’s preferable to go on with decent data that can be enhanced over time.
The CEO of a well-known retail company met every month to discuss the status of several strategic projects. Each of these projects was overseen by a different vice president. Each leader had their team prepare an update for the executive team to deliver at this recurrent meeting. These monthly upgrades grew in complexity, requiring the involvement of many team members and taking a significant amount of time each month.
Additionally, the CEO began to see statistics that disagreed with one another and other troubling inconsistencies between the various updates.
Because they wanted to unify their strategic efforts around the same KPIs, the retailer’s executive team determined that they required a single version of the truth. Additionally, having a unified perspective of the correct metrics would minimise the chances of anyone initiative leader manipulating their team’s performance for personal gain. In this way, the CEO ordered that all data used in the company’s business intelligence platform be used to educate the meetings. In addition, he prohibited the use of any supporting papers or data derived from arbitrary analytic tools (slides, spreadsheets, reports).
As an alternative, each initiative had its own real-time dashboard, which consisted of a few basic graphs and a predetermined set of leading and trailing indicators. A more data-driven discussion was created, more cooperation was encouraged, and quicker decisions were made thanks to this new methodology, which enabled everyone in the organisation to speak the same language as they assessed the success of their strategic objectives. Additionally, the executive team discovered that they were more tightly connected and focused on accomplishing their strategic goals.
Most companies’ current biggest problem isn’t a data shortage but choosing which statistics to pay attention to. It’s easy to feel data-driven but not really be data-driven when most businesses have numerous data systems and a plethora of data to pull from. Separating your company’s strategic signal from its operational noise necessitates creating a single version of the truth. Determining which metrics to use and from where they should be sourced is difficult since it’s also necessary to verify that they really indicate what everyone believes they do (never assume).
Establishing a single reality requires some technological know-how, but corporate leaders must focus on preventing a situation like the Tower of Babel. Your company’s employees must all speak the same data language, with aligned metrics, dimensions, and meanings to be really effective with data. To get a better return on investment, you must have a clear, unified picture of performance throughout your company. If this does not exist, there is nothing more essential you can work on.