Tipping Siloes: Integrating Data and Streamlining Processes for Efficiency
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Tipping Siloes: Integrating Data and Streamlining Processes for Efficiency

David Bessen, Director, CIO, Arapahoe County Sheriffs Office

A major obstacle facing the enterprises today is   the fragmentation of their data and databases.   The reasons for this are numerous, ranging   from un-integrated acquisitions to   particular departments seeking   a technology solution for their specific needs.   In the private and public sectors, this is a   particularly concerning issue which, if   appropriately addressed, presents the   opportunity to generate significant fiscal   and technical efficiencies, and, more   importantly, to create better experiences   for customer and citizens.  

In the commercial world, data   fragmentation often occurs as a result of   M&A activities: there is always a rush to   bring the newly acquired business units into   the financial system and to ensure that the new   employees are paid out that system. Data migrations   related to transactional systems, however, are frequently not   performed, as these tend to be more difficult and involve cultural   changes. 

 When I worked in the media industry, our company acquired   18 business units in 2006-7. Often, employees from the acquired   units were migrated to the new payroll systems within days of the   acquisition and AP/GL operations were integrated within a few   months. Customer-facing transactional systems, however, were   typically not integrated into the systems used by other business   units. They became data siloes, with any corporate reporting done   through manual spreadsheets and journal entries. This model of   integrating acquisitions is not uncommon in many companies.  

In the public sector at local level, departments and elected   offices are frequently very independent. Either these departments   have their own IT groups which are not coordinated with   enterprise IT or IT responds to a specific departmental request   for a solution and IT delivers it. In all of these cases the result is   the same: data is isolated, fragmented or “siloed.” For example,   departmental siloes resulted in the deployment of four distinct   electronic document management systems (EDMS) within the   county where I work; each of the departments had requested   an EDMS solution at different times with different   business requirements and no one insisted on   standardization.  

In both the private and public sectors,   the cost of data siloes is high: there   are both direct costs, such as the need   to support multiple EDMS systems,   and large opportunity costs due to   data not being used effectively, the   lack of standardized report and data   structures, or the inability to understand   the business. So why it is that data siloes   are allowed to perpetuate and impede our   ability to leverage ‘big data’, when there are   few technical reasons that prevent the siloes from   being knocked down?  

In short, the answer is ‘culture.’ In the case of business unit   acquisitions, integrating transactional systems would necessitate   the change of workflows and configurations in the transactional   system(s). The effects of such changes could be enormous: it   might require re-thinking product pricing models or how   customer interactions should take place. Historically, we have   shied away from change management, even if the benefits of change are substantial and the costs of   maintaining legacy practices are high. In the worst cases, nonstandard   systems result in poor corporate reporting with a flurry   of spreadsheets and hours of manual effort to report financial   results.  

In the public sector, there is no immunity from the reticence   to confront cultural change. We, too, are fearful of changing   business processes. When it comes to integrating data, we are   conscious of governmental transparency, yet we are hesitant to   share data across departments or between agencies. There are   exceptions. Data about criminal justice cases can be shared,   following specific compliance rules, between the federal, state   and local law enforcement agencies. But, for the most part, public   sector siloes are stout and the effort to tip them over and make   data accessible has been limited.  

To leverage enterprise data more fully, what is needed is a   concerted effort to confront cultural change and to secure small   ‘wins’ demonstrating the tremendous power that using data   smartly can offer. A few examples from my experience will   illustrate the potential of leveraging data. 

 At a business unit within a large media company, there was   a sales director responsible for subscriptions who realized that   his marketing and sales operation was suffering. His strategy   was to increase his marketing spend because that strategy had   worked in the past. Only now it was not working and there was   a demand to improve the bottom-line. Realizing that only a datadriven   argument would persuade the director to abandon his timehonored   strategy, the corporate IT department worked with him   to build a data warehouse and data marts to analyze demographic   and historical subscription data. We then taught the sales director   how to use the query tool and encouraged him to slice and dice his data, looking for ZIP codes and demographic clusters that seemed   to have atypical sales and marketing costs. Within a couple of weeks he found the answer. There was one ZIP code in which a contract sales force was selling new short-term subscriptions and   the customers were never remitting their payments, resulting in   a product being given away gratis and a sales commission being   paid. The total cost to the business unit: $750,000 annually.   Once this practice was stopped and that subscription offer was   eliminated, the hemorrhaging of cash also stopped. By merging   customer and demographic data, the director was able to use data   toisolate the problem and create an action plan to address the   issue, in lieu of just spending more marketing dollars.   In a recent public sector example, the combination of aid   recipient data and Department of Motor Vehicle data has allowed   our county to realize significant cost savings while at the same   time delivering aid benefits to needy citizens more quickly.  

With the implementation of some inexpensive technology   and a single, concise workflow that relied on “mashed up”   data from the State-wide aid system and the DMV, IT was able   to deliver a solution. Now, when an aid applicant comes to the   County, a reception clerk can swipe a driver’s license, querying   DMV records to confirm the applicant’s residence. Concurrently,   a second query goes against the State’s aid recipient database to   determine if the aid applicant has received aid previously in the   State or if he/she is a new applicant. The supporting documents   submitted by the applicant are then scanned into the applicant’s   record and the entire package is forwarded to a case worker for   review. Following the review, an interview with the applicant is   scheduled and aid is either approved or denied.  

The new process can now take as little as 30 minutes from   the time of application through the scheduling of the interview,   down from five to ten days, as a result of combining all the data   in a digital workflow. Previously, documents were photocopied   and scanned into the EDMS system; residency was determined   by the documents, which required manual review; and the   determination of previous aid also required a manual look-up in   the State system of record. With the new process, nearly 10 FTEs   are saved annually and aid applicants can be interviewed hours   after applying.  

Challenging the change-resisting retort of “we’ve always   done it that way” allowed us to develop a single, generic digital   workflow instead of 70 different workflows for each unique type   of case. In this instance, a small, yet significant, change, facilitated   the quick review of cases saving time, effort and providing better   service.  

Why haven’t we pursued changes to use technology effectively   and to serve customers and citizens better? It’s all about people   and our inherent discomfort with change. Combining data and   implementing optimized processes is scary; change is more easily   avoided than embraced. Changing that culture by presenting the   realm of the possible and achieving incremental successes, which   demonstrate the efficacy of the changes, will move us forward   to better service for our customers and citizens at lower cost—   which should be the desire of every CEO and public servant to   offer and every customer or citizen to receive.  

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