Understand the importance of data in a Selective Data Transition and what dangers exist for companies who make the move to SAP S/4HANA too quickly
Please Mind the Gap: Making the Move to a Data-Driven Culture
Insights can inform almost any decision. The challenge is in uncovering them in a suitable timeframe, and the move to data-driven cultures is only helping.
There’s always an occasional nugget of gold to be found in the Harvard Business Review (HBR). One uncovered treasure came in the form of an article entitled: Is Your Business Masquerading as Data-Driven?
It’s an interesting read, particularly given our current circumstances in the days of COVID-19 and the fact that most businesses are navigating completely unchartered territory. Data now more than ever needs to stand up and be counted. Decisions need to be informed, strategies adopted, and new opportunities identified – hence the almost frenzied search for insight amid the detail.
But as the HBR article highlights, there’s a problem. Well, a gap, really - a gap between the perception that data is increasingly well-controlled, managed, and exploited, etc., and the reality of current data cultures.
A Split in Expectation
As the article highlights, global spending on technology and services for data analytics is around the $40 billion mark. Look elsewhere, and the numbers keep on coming:
- $135 billion – is the predicted market for data and analytics by 2025
- Investment in data quality tools is predicted to reach $1.3 billion by 2022
Yet despite such investment, many executives still admit that they’re not making the most of the data at their disposal. For example, a Deloitte report on the topic suggests that the majority of businesses are not insight-driven. At the same time, 67% still lack basic data infrastructure – and continue to work in silos.
The Cultural Dimension
However, returning to the HBR article informs us that the gap between perception and reality is less about technology and more about internal processes and culture. It also looks at the behaviors that such a gap produces and names the worst offenders:
- Employees making decisions based on averages and treating customers, suppliers, and other stakeholders as a generic whole
- The “my version of the truth is better than yours” syndrome and the limits this places on decision-making
- Misguided incentives, which only serve to reinforce all the wrong behaviors to begin with
- Decisions preceding data, where the role of insight is simply to support an individual’s gut instinct.
Applying a Business Context
Such behaviors also help show that being data-driven isn't enough by itself. Certainly, it’s an enviable goal, but as organizations pivot toward a new reality, the emphasis also needs to be on ensuring digital transformation projects are business-driven.
For example, one such project could be aimed at digitalizing the complete purchase-to-pay process. This would certainly make sense for delivering a more responsive and efficient finance function.
But creating the data alone should not be considered a worthy use of resources. Instead, thought should also be given to the business processes that can be optimized because of the activity – or aligning the insights now available with broader strategic objectives.
Getting Data Literate
However, embedding a more robust data culture can be easier said than done. Certainly, such an initiative needs to be driven from the top down. Otherwise, it’s difficult to avoid treating data as a resource or commodity that’s only relevant to specific parts of the business.
Gaining executive buy-in, though, is made easier by the provision of a sizeable carrot: the ability to make better decisions. Hence the importance of improving data literacy at all levels of an organization, a task that, according to Gartner, should ideally be driven by the Chief Data Officer (in fact, they believe around 80% of companies have already made a start).
What’s more, data literacy is essential because it helps extend the utility of corporate data. It also helps companies review the information resources currently available to them – and to recognize what’s valuable and what’s not fit for purpose. Responding to the next significant business disruption will be a lot easier if insights are available at EVERY point of need, if they’re accurate, trusted, and (just as importantly) understood!
Data comes at a cost. Organizations have to pay for their collection, cleansing, hosting, and maintenance, as well as the salaries of data engineers, scientists, and analysts. However, such investments can be called into question when the insights are not immediately available to support businesses through particularly trying times.
It should always be kept in mind that insights can inform almost any decision. The challenge, of course, is in uncovering them in a suitable timeframe, and the move to data-driven cultures is only helping in this regard. Add in technologies like Syniti Knowledge Platform and its ability to help build, structure, and share information, and it’s a task that’s getting easier by the day.
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