Here are a few examples of our previous engagements with clients and our findings. To learn more about our smaller scale tinkering, check out our Thought Leadership page.
The real estate division of a global bank was facing rising costs year over year outpacing the increase in their workforce. A comprehensive review of the group’s portfolio of over 2,000 buildings and approximately 100,000 employees using traditional methods was deemed unreliable and costly. CKM was invited to conduct a digital analytics review of real estate utilization and identify savings opportunities.
In order to determine on-site sign of life, multiple data sources were linked, ingested, and analyzed to develop digital footprints containing employee presence and location. Aggregating employee digital footprints enabled measurement of on-site attendance, which was compared to predicted values. This revealed discrepancies between allocated and utilized seats. The proposed desk reorganization was able to generate savings opportunities of over 9% while also providing the real estate group with improved visibility into real-time real estate utilization.
Improvement opportunities not visible through traditional methods by utilizing actual presence information were uncovered. Proposed seat allocation plan reflecting remote working behavior reduced rented floor space by 9%. The client was provided with reporting tools for ongoing analyses and to maintain real estate efficiency gains.
The IT organization within a Fortune-500 firm was responsible for managing 3 million application, infrastructure and end-user incidents per year. While management teams had implemented a series of rolling improvement initiatives, the organization was struggling to achieve the desired level of operational performance and efficiency. Existing reporting was primarily static, highly aggregated and provided mostly high-level averages on historical data. The executive management team and line managers wanted to move towards more data-driven decision-making.
Incident and related data were scattered across multiple disconnected systems, which prevented existing reporting and analytics tools from providing a comprehensive view of activities within IT operations. The CKM team established an analytics environment that incorporated static and dynamic data feeds from across the organization.
The CKM team focused on data integration and quickly identified a range of tangible opportunities for performance improvement. Analytics included process mining to identify inefficiencies in the routing and handling of tickets. Natural language processing techniques were also used to identify previously undetected recurring patterns in incident activity, which in turn led to the identification of deeper technical root causes.
CKM was able to provide management with a targeted program of actionable initiatives to improve both the operational performance and efficiency of the organization. Executives and line managers were quickly able to move away from high-level ‘best practices’ towards data-driven decisions that reflect the unique nuances specific to the organization. These insights were based on factual near real-time measurements from data that already existed with the organization.
To support the implementation of these insights, a series of interactive dashboards was developed to allow for continuous near real-time monitoring and decision support. Giving managers the ability to interactively explore automatically refreshed analytics output helped introduce a fundamental shift in how the organization made daily decisions and developed future strategies.
A multinational minerals and mining organization was in the midst of a multi-year plan to improve contractor management operations. The organization’s contractor management group was tasked with identifying cost savings through:
The group had been struggling to improve the productivity of both internal and contractor resources in managing business requirement and invited CKM to conduct a Digital Analytics review of current contractor management.
CKM Advisors reviewed over 14,000 contractors across 19 sites to identify opportunities for effectiveness and efficiency gains.
From the onset of the engagement, CKM collaborated with the client to identify the areas for greatest savings impact. We began by identifying relevant operational, financial, and health and safety data sources to include in our analysis.
Successfully performing text analytics on gate-access and human resource systems allowed us to develop a more realistic resource baseline and monthly contractor growth curve. A high turnover rate was identified, highlighting the volatility of contractor usage within the organization.
Additionally, combining A/P and maintenance systems uncovered that there were discrepancies between onsite hours and invoiced hours. In fact, productive time accounted for only 73% (excluding travel time) of contractors invoiced hours. On-site managers due to production concerns had ignored discrepancies.
Based on our analysis, potential savings opportunities of approximately 28% were identified by improving visibility into contractor activities and billing practices. Our analysis was well documented and remained within the client’s environment to allow for future studies to build off our improvements.
A global, diversified financial institution was struggling to onboard its new and existing employees and contractors smoothly and consistently. The process was frequently delayed, depriving personnel of the necessary tools to perform their job functions. The resulting decrease in productivity, along with immeasurable opportunity costs due to foregone benefits and delayed projects made this a top priority for the organization. Previous initiatives attempted to bring this process under control, but repeatedly fell short of the desired level of improvement.
Given the extensive effort that had already been invested into fixing this process, CKM began by reviewing the previous work and identifying the complexities that needed to be overcome in order to achieve project success.
We discovered that onboarding data was scattered across disconnected systems owned by different support functions, including HR and IT, which hindered prior attempts to establish a comprehensive view of the onboarding activities. This was complicated by the fact that the onboarding process was formalized after the systems had been established, which resulted in multiple system dependencies and nuances that needed to be considered.
Additionally, due to the movement of employees within the bank across lines of business and geography, the regulatory, technical and organizational restrictions converged to form a process that was challenging to navigate and even more difficult to manage.
We conducted a thorough analysis of onboarding data using process mining techniques. CKM found that although the issues leading to delays were unique and localized in systems, the onset of delays was predictable and could be addressed ahead of time.
From this, it was determined that a satisfactory resolution could be achieved only if the solution could engage and satisfy the needs of all stakeholders across HR and IT, could analyze the technical and regulatory dependencies in real time, and could be used to resolve numerous unique issues.
CKM built an analytics environment that would give managers the ability to interactively explore automatically refreshed analytics output, including interactive dashboards that would allow for continuous near real-time monitoring and decision support at a granular level.
The environment incorporated static and dynamic data feeds from across the organization. As part of this environment, an onboarding analytics platform was developed to predict the onset of onboarding delays based on historical process data. A monitoring queue was established that would be able to respond to each unique issue in real-time using the platform. Furthermore, the platform provided a holistic view into the onboarding process, allowing permanent process improvements to be developed and executed by system owners.
As with all of CKM’s work, all code and algorithms developed were shared with the client, allowing in-house teams to continue running analytics after the conclusion of the project.