Fostering Right Interactions and Level of Engagement with Collaboration
Collaboration inside and outside organizations is becoming increasingly important, as it becomes core to business processes. Conversely, many organizations are unsure how to measure and manage collaboration effectiveness. Many methods and tools are effective in measuring and managing individual’s work performance within organizational networks. But they are challenged in understanding the implicit interactions occurring within these networks people rely to complete their tasks on a daily, weekly, quarterly, and annual basis.
Many organizations have reacted by investing in various collaboration tools. Technology only begins to solve the issue. Companies often struggle with whether collaboration improvement efforts are actually increases an organizations value or just another investment that did not live up to expectations. The measuring and managing the value of collaboration initiatives comes when organizations start capturing and connecting the implicit interactions to business outcomes. To do this, organizations must gather and analyze how, when, what, and why employees, supplier, and partners interact, as well as linking them to specific outcomes.
What organizations need in this digital age is to capture, collect, and analyze the value created by implicit interactions within their organizational networks? Analytical methods must be adjusted to assess the costs and benefits of these interactions generate as well as any opportunities to improve the touch points linked to the overall business value. Once the value traversing the networks is better understood, companies can effectively influence and manage interactions with their organizational networks. This can help reshape organizations, reduce complexity, and improve customer and employee customer experiences.
Collaboration solutions supported by data and analytics help companies to identify those critical touch points where improved interaction creates value by removing connectivity barriers
Data and Analytics can help by identifying the areas or tasks where interactions are most significant and then link those to business decision-making and outcomes. The majority of the data is unstructured such as emails, SMS, capturing conversations, employee time tracking, project tasks, operational tasks and surveys. Now organizations can create interaction maps illustrating how individuals and groups relate to one another to complete activities.
The result is collaboration approaches and tools combined with data and analytics can help companies improve individual, team, and enterprise-wide performance. It turns out that high-performers typically have strong relationships with critical implicit interactions and also considered the most productive. As collaboration is conducted analysis could help reveal distinction between the strongly and poorly performing groups by getting to the root cause of both high performers and low performers. Then high performing attributes and activities can disseminated to other groups within the organization.
For example, solving operational issues quickly often requires collaboration across teams such as applications, middleware, networks, compute, and databases. Teams start by passing information and interacting back and forth to hone in on the work around and then the root cause. Many times after the issue resolution, some the key interactions are lost. The keys to improving collaboration in this situation could be to capture not only the activities and tasks but the implicit interactions related who and how the work is actually completed. This gives teams’ better information to help improve identifying and preventing potential operational issues. Also continually measuring collaboration and promoting cross-team engagement can result in overall team performance.
Collaboration data and analysis also helps organization leaders to prioritize their investment in collaboration solutions through providing insight in to the cost and benefits improving specific business outcomes. For instance, understanding specific interactions that improve individual and team productivity would be far less costly than purchasing another underutilized collaborative tool.
Another example, is calculating the average collaboration cost per employee. This analysis can help organizations identify collaboration inefficiencies. By looking at individuals who are considered good collaborators, companies can pinpoint persons who not are effective than the good collaborators. So now the company better informed on how improve overall collaboration before purchasing another tool. Instead they may consider investing collaboration training.
The results of identifying and promoting high-performing collaboration are just the tip of the iceberg. As organizations mature then can manage down the interaction level to improve the top line as well as productivity. Targeted changes designed with specific outcomes can be more effective than broadly pushing enterprise-wide collaborations changes, which could yield lower productivity and little to no cost improvements. Collaboration solutions supported by data and analytics help companies to identify those critical touch points where improved interaction creates value by removing connectivity barriers.
One last example, companies can avoid product design and operational issues by involving its application and infrastructure architects throughout the product life cycle. Unfortunately, to this day this is not always the case. Under typical IT/project budgeting and cost allocation approached, it could appear that multiple IT architects are needed. Conversely, collaboration analysis may show that IT architects are less interactive than other employees. So the first option is break down the collaboration barriers that inhibit the IT architects from engaging with their colleagues.
Collaboration is becoming essential aspect in today’s increasingly digital businesses. But when companies deploy collaboration solution without understating how, why and when people interact with customers, colleagues, and suppliers as well as associated costs and benefits, they reduce their collaboration effectiveness. A collaboration data and analysis perspective gives organizations the information they need to foster the right interactions and level of engagement where it delivers the most value.