If you haven’t noticed, we’re in the age of big data. Companies are gathering data from the marketplace faster than ever before, storing if for future use, to extract business intelligence and develop personalized relationships with customers. Helping to support the movement, customers are ready to share their information with trusted brands as the perks are too attractive to resist.
Once that data is captured, data management is needed. The optimal situation is perfectly harmonized global data shared by a variety of interested individuals who never disagree on the content. When ERP implementation is involved and multiple business units have to merge into a single instance, this ideal situation is never the norm.
According to a recent blog post from data management provider BackOffice Associates, there are three trends that tend to emerge in these situations. First you have the oldest child syndrome where the first country involved spends a considerable amount of time and then believes any later deployments should follow its lead. A sense of entitlement ensues, as well as the perception that its users have a better grasp on the system instead of the potential for later deployments to learn from their mistakes.
Next, data narcissism can set in as in-country users are accustomed to a certain level of autonomy in relation to the master data. Data governance is generally a foreign concept and they tend to resist any red tape applied to their process. If something appears to be wrong, a fix will be applied for a single order without regard to how it affects the process, others users or data management.
Finally, the opposite of data narcissism is tragedy of the commons. Once the data is accepted as global data, ownership gaps and local disengagement can emerge. When problems emerge, local teams could take the, “not my problem” attitude until a global data quality issue emerges, creating a bigger problem that the one they refused to address. In each situation, the policy that all data is local can help mitigate these unnecessary problems.
Still, it helps to implement a few steps to help keep these tendencies at bay, including clear escalation points, bidirectionally, between local and global teams. Here, it’s critical that local teams can efficiently points to issues with global resources and that those resources can quickly clarify the information needed from local resources. To support this fully, clear and detailed ownership must be published and granular to eliminate the gray areas.
Efficient resolution processes ensure the timely resolution of issues raised so as to avoid a negative business impact—as do accountability through persistent data validation and accurate audit reports. These elements have to be in place when data management becomes a global focus with the involvement of the local team. It’s often not considered until problems arise, but getting ahead of the issues can minimize them and allow your teams to focus on the targeted outcomes instead of putting out fires.
Edited by Alisen Downey