Business process improvement is one of the biggest drivers for digital transformation. However, it's a vague term, so what exactly does it mean? What are the biggest business process improvements that organizations typically see with digital transformations?
When we go through digital transformations, most of our clients want to improve their business processes. They want to automate, have better visibility, be more efficient and effective, provide a better customer experience, a better employee experience, and manage their supply chains better. These are just a few of the reasons why organizations go through digital transformations.
Today, I want to talk about the most common business process improvements, as well as the improvements that offer the greatest opportunity for business value within digital transformation. It's important to understand this so you don't lose sight of the potential value that you could be getting out of your digital transformation.
The first and most common improvement that organizations expect to see in digital transformations is automating manual processes. This is often the first thing that comes to mind when organizations think about their digital transformations, and it is often the lowest hanging fruit. It is the easiest thing to address as part of your transformation, which is why it is the most common.
When we think about automated business processes and getting rid of some of those manual processes that you have in place now, that applies to a whole host of different functions and business processes within your organization. It can apply to your marketing automation, the way you manage and track your sales force, your supply chain management, your manufacturing, your warehouse management, inventory management, procurement, and all those different components of your business can be automated. You can take away some of those manual processes, those spreadsheets that you are using to track data and manipulate data; all that stuff can go away. You can start to look at ways to get rid of those manual processes so that your employees can spend more time managing exceptions and doing more strategic work as it relates to their day-to-day business processes.
Now, if we look at any sort of enterprise technology, whether it's an ERP system, CRM, human capital management, supply chain management, or manufacturing execution, a lot of those different types of technologies are starting to use machine learning as a way to further automate manual business processes. In other words, they're taking highly repetitive, redundant business processes and using automation to automate those processes and to do some of the thinking behind some of that more mundane work. This means that employees don't have to manually transact all the stuff that they're transacting today.
For example, if you're in the accounts payable department of your organization, instead of processing each and every single purchase order that comes in, machine learning can learn what the common, normal purchase order processing might be. This means you can process those for payment, and it also knows when there's an exception or an anomaly that needs to be flagged for human intervention. This can eliminate 70%, 80%, or even 90% or more of the manual work that maybe humans were doing prior to automation. This is just one example of many that organizations are doing to enjoy the benefits of automation as one of their key business process improvements.
Another key business process improvement that organizations often realize from their investments in digital technologies is centralized visibility to information. Instead of having to manually search for data, go into different systems, ask people, or look in spreadsheets or manipulate data to get the data they really want, now they can have centralized visibility into a whole host of business processes and outputs from those business processes. This is something that can be a game changer for a lot of organizations, not only because they're spending less time manually searching for that data, but because now they have easier access and more real-time access to that data. This means they can make better decisions and have better visibility, understanding, and insights into what is making their business run, what's working well, and what needs to be improved.
Some of the specific technologies and functions that technologies can provide in today's enterprise technology space include the world of dashboards and business intelligence. You can look at tools like Microsoft's Power BI or Tableau, which are two business intelligence tools that can bolt on to other systems to provide that sort of visibility. You also have enterprise resource planning (ERP) systems that provide end-to-end business processes, but also provide centralized reporting and business intelligence to consolidate all the data being captured in their systems. These are just two examples of the types of technologies that are enabling the sort of visibility into enterprise-wide data.
Another common business process improvement that organizations often realize from their investments in digital technologies is improved financial consolidation. This is partially based on the efficiency gains that have already been discussed, but it is also based on the ability to consolidate data across the enterprise to obtain the necessary financial results.
If we look at some of the larger organizations in the world, we find that they dedicate a lot of manpower and horsepower to closing their books every period, whether it's monthly, quarterly, or annually. They often have large teams of accountants performing manual processes and journal entries and going through data to provide that financial consolidation. Therefore, having efficiency, effectiveness, and accuracy in data is crucial from both a business value perspective and a regulatory perspective.
For many organizations that are publicly traded or have investors who expect real-time and accurate information, this can be critical from a regulatory perspective. Thus, financial consolidation and better financial consolidation are among the more common business process improvements seen in organizations undergoing digital transformations.
Now, the first three business process improvements that I have already talked about are what I would call "incremental" business process improvements. They can be very significant and material, but they only scratch the surface of what technology can do and what the potential business process improvements could be. So, if we shift gears and work our way up Maslow's hierarchy of needs, we can now start to look at really innovative ways that we can restructure our organization. One of those ways is through a shared services model.
Larger organizations that have grown through acquisition or organizations that have multiple locations often have built up redundant competencies throughout the organization. In other words, they have multiple departments doing the same thing. If they were to consolidate those functions and have more of a centralized shared services model, they could save time and money and have a more consistent way of doing business. For example, many organizations find that functions like accounting, HR, IT, and procurement are redundant throughout the organization. They are spending too much time and money on people doing the same exact thing. Even though they may be doing the same exact function, they have different ways of operating.
What organizations are doing in many cases is saying, "We're going to move to a shared services model where we're going to centralize and consolidate our HR, IT, finance department, or whatever department it may be, and we're going to have a common operating model. We're going to use the same toolset, reduce our workforce, and have fewer people doing more because we're centralizing that function." That can be a big game-changer in terms of saving time and money as well as becoming more effective in the way they conduct these business processes.
With the advent of predictive analytics, artificial intelligence, and other quantitative technologies that can help provide more meaning behind the data that organizations capture, they are also finding that they are able to plan and predict for the future better. This is because they have better accuracy of data and tools like AI and machine learning that can help them make sense of that data and even anticipate future outcomes based on past events. This allows organizations to have better planning processes.
For instance, financial planning, demand planning, sales and revenue forecasting, manufacturing planning, procurement planning, and inventory management, which require making decisions about the future before having 100% certainty of what will happen, can be automated and streamlined to become more effective as a result of AI, machine learning, and other enterprise technologies that provide visibility.
Another area where these tools are extremely relevant is supply chain management, where broken supply chains, bottlenecks, and unpredictability are common issues. Having better access to data and tools like AI and machine learning can help navigate that uncertainty more clearly. Many organizations struggle with their supply chains because they don't have the proper tools and data to help them plan for the future. This is why supply chain management is a potential business process improvement that can be a game-changer and deliver a huge amount of value in your digital transformation.
At the end of the day, one of the business processes that can be most improved with digital transformation is better data management. It may sound mundane and technical, but the troubles that many organizations face are related to data accuracy. In some cases, this is due to a lack of the right tools, such as BI and machine learning, which we've already discussed. However, inaccurate data can also be caused by a lack of data governance controls. To take advantage of AI, machine learning, predictive analytics, and business intelligence, we need accurate data. Therefore, master data management and overall data management, including transactional data management, can be critical business process improvements that can deliver a lot of business value and effectiveness to an organization as part of its digital transformation.
If you are looking to strategize an upcoming transformation or are looking at selecting an ERP system, we would love to give you some insights. Please contact me for more information firstname.lastname@example.org