Evolution has been taking place in the world of business process management for the last five decades. The highly sophisticated BPM software solutions of today is a product of years of evolution of management practices. Over time, cross-influences between different theories of management and computer science, and the urge to find better ways to leverage data for business effectiveness resulted in the invention of BPM Software.
Business process management can be seen as an extension of Workflow Management (WFM). However, WFM focuses primarily on automation of business processes while BPM digs deeper into the broader support – for example by supporting business intelligence, simulation and case management, among other things.
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BPM Software: Beginning of the Revolution
Both the 1960’s and 1970’s marked critical eras for business managers. Although the pieces of information systems they had would not allow a non-programmer to perform complicated data analysis and generate reports that would aid in decision-making, there was some good progress.
Companies and researchers were developing tools that businesses could use to access and extract data from mainframe-based batch systems. However, these tools required specific technical expertise that many businesses of the day didn’t have.
And, more poignantly, the business information systems stored data in a way that would lead to massive inaccuracies, resulting in partial records, missing values, inaccurate information, misspelled information and much more.
So, two things – low quality of data and lack of technical expertise (programming knowledge) that hindered the success rate of BPM systems during that period.
Developments During The Industrial Age 1960’s
Businesses’ use of technology for managerial analysis that informed decision-making gathered steam by around 1950s-60s. This is the period when the corridors of academia and practitioner circles begun adopting management information systems (MIS) as a body of knowledge – and a tool that could possibly help leverage computers for corporate management.
During those times, organizations had not fully utilized the computing power of the day to manage and process and analyze data. The MIS thinkers envisioned an environment that elevated the use of technology from the clerical administrative data processing to a more advanced user. As a result, such computer systems would provide a corporate-wide integrated interactive environment that managers could exploit for analysis and decision-making.
The foundation of this new, ground-breaking capability would be a ‘data hub’, or a ‘data base’ – the ‘data safe’ where enterprise-wide data would be stored in an integrated manner. However, the kind of functionality envisioned by MIS thinkers predated the required technology. By 1960, technology wasn’t sophisticated enough to deliver such interactive and clean data integration.
During those times, managers relied on mainframe-based batch-oriented report generators. These systems used querying modules to generate structured periodic reports that would help managers in decision-making.
However, there were also file management software that was used in ‘data processing’ departments – IT departments of those times. However, such solutions were developed to ease the burden of technical staff and data analysts and were not tailored for use by business managers. Besides, generating the simplest of reports, actually, out of the accounting systems would call for the heavy involvement of the technical staff.
The arrival of cheaper and more powerful mini computers was a good news and an opportunity integrated business management evangelists of the day to achieve their visions.
Researchers with access to these new computers begun experimenting, developing and implementing better technological solutions for modeling and decision support. At the same time, the MIS theory evolved to understand and accommodate human-computer interaction in the information-system based decision-making.
Now, it is the confluence of these developments that resulted in the birth of new business information systems christened Decision Support Systems (DSS).
Decision Support Systems were defined as computer information systems that offered support both for unstructured and semi-structured managerial decision-making.
During that period, various prominent researchers and thinkers came up with different concepts of DSS model and helped implement the early models for different applications – portfolio management and product pricing during the early 1970s.
Informational Age – (1970’s – 1980’s)
The major technological feat that brought about a great change in the industry was the invention of the microprocessor in the year 1972. It led to increases in computing power while at the same time diminishing the size of the computer.
With the processor fitted in a very small chip, it reduces the cost of production which meant computers could be developed and made available to the public. Besides, different companies and researchers had come up with interactive information systems that would models and user data to help analyze semi-structured organizational problems.
For example, people like Michael Zisman, Skip Ellis, among others, developed office automation prototypes – Officetalk-D and Officetalk-Zero that used Information Control Nets to model processes.
Besides, during the same period, they recognized that DSS systems could be enhanced to support key decision-making operations at any level in an organization. During this time, also, DSS thinking expanded, and as a result, leading to the rise of different supporting solutions and concepts that included Executive Information Systems (that allowed managers a bird’s eye view of the organization) and also Group DSS for organizational decision-making.
But, in the late 1980s, another highly transformative technology emerged – the spreadsheet. The release of Lotus 1-2-3, spreadsheet software developed by Lotus software, allowed the end user more control of their data besides offering tools that they used for data reporting, running basic organize, process their own data and run basic descriptive analytics.
It is also during this period that structured methodologies emerged that aided in information engineering and data design. For instance, an influential author of a series of books on Information Engineering, James Martin, wanted to institute a traditional engineering like rigor and energy to the design of information delivery systems.
During this period, also, different concepts including 4GL language and computer-aided software engineering were developed. Why were this development important in the field of business information management?
The developments signaled the increased importance of data storage, design, storage, processing and analysis in the commercial business environment. They also signaled a need for managers to manage the increasing data complexity in a logical manner.
As a result, the new need lead management to the emergence of a new class of DSS systems solutions – data-driven DSS that provided solutions that allowed managers to quickly access the data, perform analysis for a data housed in a particular database or run your analysis across a series of databases – emerged.
Driven by the theory around Executive Information systems, the new DSS solutions were meant to provide data on critical success factors that top managers would need.
Besides, the new technology was in the form of relational database systems (RDMS). These database systems could allow the users to store data and easily manipulate it at will.
This new EIS concept went through a number of developments:
- The emergence of new methodologies that managers could use to measure the state of the organization, for example, the Balanced Scorecard.
- Formalization of the technical underpinnings into new mechanisms – for instance, online analytical processing, OLAP and the multi-dimensional data structures.
- Later on, in the late 80s and early 90s, the data-driven technology, and process management was rechristened loosely as ‘Business Process Management’ solutions
The 1990s: Process Optimization
In the 1990s, there was a clear revival of the ideas already present in the early office automation prototypes. For example, many commercial WFM systems developed in this period. WFM became more popular, prompting business to focus on business process re-engineering. And, about 60% of Fortune 500 companies were planning to initiate such project or had already initiated them. Like the relational database, this markets was, to a large extent, dominated by the traditional relational database vendors.
Most business liked Six Sigma, TQM, and Lean models, which took a more holistic and organization-wide approach to data. Besides, tools such as Balance Scorecards and Strategy Maps helped businesses in their strategy implementation efforts.
The greatest force behind the development and growth of Workflow Management systems in the market where the relational database vendors. This group had undergone through a period of growth after they surviving the database wars.
The more WFM and BI systems developed, the more businesses needed a better, more reliable infrastructure to help manage enterprise-wide data in an integrated manner. This need gave rise to “data warehouse” solutions.
The idea behind the data warehousing concept was to provide an architectural model that would allow data to flow from operational systems to support environments. As such, running activities that took a considerable amount of time to perform – like completing reporting requests – took a shorter time to execute.
Again, data warehousing helped bring together data that had previously been spread across numerous sources – historical respiratory of data, Online Transaction processing (OLTP) and external sources – with one querying tool.
Once this was accomplished, enterprise data could then be sorted and separated into more compressed versions of the data warehouse – the ‘data marts‘. That way, every department within the organization could easily access the specific information they are in need of.
Besides, the ‘data marts’ were designed to support more sophisticated analysis functions required for business intelligence such as online analytical process – OLAP. As a result, it allowed managers and other users to easily execute rapid and complex analytical queries.
This development led to the rise of another shift of complexity – the rise of web-based analytics. The new changes affected the sophistication, scope, and frequency of traditional Business Intelligence tools when it comes to alerts, dashboarding and report generations.
The business environments became tougher while business processes and operations increased in pace and complexity. As a result, organizations needed to initiate proper integration to accommodate the ever-increasing variety of data sets, in real-time.
Later on, the late 1990s, a more specialized system for managing business processes emerged – the business process management (BPM).
Turning Points – 2000, and Beyond
Miniaturization of devices and availability of networked computers meant the generation of tons of data. In the 2000s, businesses started experiencing an era of Big Data revolution fueled by the internet and the increasing number of connected devices.
Data capture, storage, retrieval, and manipulation became easier. During that period, a number of raw data processing platforms were adopted, including Hadoop among others.
Also, the new business landscape gave birth to new challenges that required new thinking and different processes. The agility of the mid-2000s business process management platforms underwent an intense refining process. BPM software design evolved, focusing energies on an industry-specific process – what is commonly known as software verticalization. As a result of the growth if an industry-specific system, more businesses were persuaded to adopt business process management software in most organizations.
During the same period, visualization tools also began to evolve. What it meant was that the modern platforms empowered users to perform ‘self-service access’, and possibly find a way of utilizing their data on their own without the need for training.
However, the use of pure WFM/BPM software has not been fully adopted in other industries unlike with the insurance and banking sector. However, there are pockets of WFM/BPM software that are still integrated into other systems. For instance, Oracles ERP system, SAP provides workflows engines.
Cloud-computing – The last mile for BPM?
Today, many companies are migrating some of their operations to the cloud, including BPM Software. In 2014, about 69% of businesses have a portion of their computing infrastructure (up from 57% of businesses in 2012) or at least one application in the cloud. That’s according to the 2014 Enterprise cloud-computing study conducted by IDG.
According to the study, 18% of enterprises had plans to use cloud-based computing infrastructure and/or applications in the next one year. And, around 13% had plans to get started with cloud-based applications or computing infrastructure within 1-3 three years.
In 2016 the findings from the RightScale’ 2016 study revealed that about 17% of businesses are using over 1000 virtual machines in the public cloud, up from 15% for 2015. Besides, around 31% are doing so in the private cloud, which is an increment from 2015’s 22%.
What can we learn from these studies?
The findings corroborate Gartner’s Jim Sinur 2011 prediction that, “BPM software and the cloud would be the real thunder in the future business landscape“.
Moving to the cloud has a lot of benefits for businesses. IT free up more money and reduces the many efforts business put up to run businesses on on-premise BPM software.
The speed of uptake, though, is a huge plus for cloud-based business management systems. Besides, when the BPMS is offered as a service, it gives businesses opportunities to try it out and see whether it is a right fit for their operations. And, the good this is, if they are impressed with a certain system, they don’t need to install it. Thanks to paying for use ‘subscription model’, businesses need to pay the required fee and have their BPM software system set up for their use. One more thing, it becomes easier for businesses to orchestrate the data and application that are hosted in the cloud. As a result, it increases the efficiency of your BPM Software processes.
Today, business process management is converging with a platform as a service (PaaS). That means, among other things, business will enjoy the benefits of process support and application development in an integrated model. Businesses will access a cloud-based BPM software platform that will allow them to build highly flexible, user-centered smart process applications. As a result, it helps eliminate traditional business productivity challenges.
What do businesses need to consider when it comes to cloud-based BPM Software?
- Will adopting cloud-based BPM software help you achieve what you want to achieve today, next week and in the future?
- Are there any services or data in the cloud that processes must work with?
- Are you really decided about running processes in the cloud? If so, how will you include systems that are not in the cloud and any other pre-existing data?
Impacts of cloud-computing on BPM processes
- The ‘mess of many’ dragon: There is one great challenge most businesses have to workaround when it comes to adopting both cloud-based and on-premise BPM software solutions – the ‘mess of many’.
Why is it scary?
It makes it very difficult for businesses to create enterprise-wide processes across different departments, or systems in the organization without duplicating their processes. Today, cloud BPM software solutions mean businesses can maintain consistent processes across the business departments. For example, you can choose to have project management software that runs in the cloud and still keeps your HR or ERP systems run on-premises.
- ‘Mashing up’ concept: The other impact of cloud computing on business process management systems is the idea of mash apps. Mashing up helps process information with data from the cloud and on-premise applications to come up with process-centric composite apps. It is a concept that is becoming important as the end product for business process management.
The market for business process management continues to evolve as the cost of technology falls further. BPM Software has evolved from the mechanical batch-data reporting of the 1960s to the sophisticated FWM/BPM software systems of today. Besides, the rapid growth of cloud-computing means businesses (or, more users) can deploy, and use technology without involving the geeks.