5 ways a digital twin of your business will help you navigate the new normal

Christian Pedersen Profile picture for user Christian Pedersen May 20, 2020
Enterprise software is changing, becoming a 'digital twin' that maps your business and helps you choose the best route, writes Christian Pedersen of IFS

Business woman in VR headset while twin consults business data © ImageFlow - shutterstock
(© ImageFlow - shutterstock)

When I think about the way I have consumed technology in my personal life, there's no doubt the pace of disruption and change has been rapid.

Google Maps for example, has changed the way we get around. It has done this by creating a 'digital twin' of the real world using a tremendous amount of geospatial data. This shows us our geographic location, the direction we are moving and helps us find where we want to go and how to get there. If only we could say the same thing about our enterprise software!

We are entering a period where executive teams may start to feel they need more and better business navigation tools, as they constantly re-assess unfolding conditions and move opportunistically. Current global conditions look set to become the catalyst for systemic digital transformation as every chief executive officer seeks a 'Google Maps' of their business and the optimal routes to follow. And this is where mapping enterprise data and processes into a digital twin — an accurate, constantly updated digital representation of the business — may pay off.

1. Map the business

To find their way, a CEO will need more than a static map or visualization of the process flows of the business. She or he will need a true digital twin of the organization. Certain enterprise systems today include operational intelligence tools that enable executives to map the pathways value takes through the organization. This operational intelligence system must be configurable so a management team can structure the business dynamically, describing process and value flows between different internal entities and transactional partners. This structure must directly configure underlying transactional systems including enterprise resource planning (ERP), enabling rapid business process change in real time based on unfolding business conditions and requirements.

This form of enterprise operational intelligence has already been productized and I expect to see this embedded deeply through application sets in the future, possibly even as a pathway for artificial intelligence (AI) functionality to automate the business as a whole.

Using this analysis, enterprise software will come to proactively make recommendations for action based on real-time transactional data. This 'guide-by-the-side' approach to AI will in time yield to full robotic process automation so executive teams can manage by exception. This will be a natural progression as executives come to trust this internal business map, and the turn-by-turn guidance it offers as they discharge their fiduciary obligations to the company.

Today, a modern enterprise system will make broad use of automation based on static setpoints. A reorder process may be activated when inventory levels drop below a certain level. Software may initiate a contract review if a supplier's financial condition suggests they may become insolvent. But rather than static triggers which are a fixed point, the business map is a three-dimensional representation of the enterprise, enabling decisions based on multiple dynamic data sets.

2. Deliver operational intelligence

In this digital twin model, we may find ourselves thinking less about business intelligence and more about operational intelligence that enables executives to model in real time the outcomes of various business decisions and then operationalize those decisions in the underlying transactional systems.

Enterprise software built for operational intelligence will go beyond displaying information from published data cubes to dynamically making decisions in real time based on enterprise data, predictive modeling and a representation of the organization's goals and values. Software will also increasingly rely on packaged cognitive services designed to solve specific types of problems in business, and on access to external datasets on the public internet or proprietary services.

This robust data set and contextual approach to data lets the software hide tremendous complexity while enabling decision makers to act on the information, either by submitting a recommended course of action to an executive or through robotic process automation.

3. Packaged systems for rapid time to value

Enterprise operational software is making inroads in sectors like local government, where a smart city improves the customer experience for the layer of government that touches most people's lives the most directly. Stephanie Weagle describes here in SmartcitiesDive how municipalities are able to harness tremendous amounts of unstructured video data in order to balance load across various resources and create operational intelligence. The private sector too will need to identify the data sources, from their own transactional systems as well as external open access and proprietary data sets, that can be used to create complex and interwoven data and process flows that create value for customers and stakeholders.

But most businesses just don't have time or resources to manage the overhead of such a system, so proprietary commercial-off-the-shelf (COTS) solutions are required to shield us from this complexity with a user experience that frees executive teams to continually focus on leading indicators and move the business in the appropriate direction.

4. New leading indicators

And executives now have new indicators to watch — things like The COVID Disruption Index, or for that matter more direct and localized figures like new infection rates and unemployment rates.

According to economist Richard Baldwin in the Chicago Review, in the immediate term, executives will need to monitor three ways the pandemic impacts the economy:

  • Decreases in output caused by workers 'downing tools' or being sick. This according to Baldwin will result in a corresponding drop in consumption because workers in countries like the United States where many workers have no sick leave and those working in the gig economy.
  • Public-health measures including factory and office closures, travel bans and quarantines will present logistical challenges that must be managed and may be seen as indicators of coming reductions in infection rate.
  • Expectations shocks as the level of uncertainty in the current environment results in reticence to make investments or future commitments as reflected in purchasing manager indices (PMIs).

Monitoring conditions as they unfold and adjusting the business from a strategic and tactical standpoint in real time will really require more of the business to be simplified and automated during the current disruption as well as during a new normal that will likely be characterized by even greater volatility than recent years.

5. Progressive disclosure

Automating elements of business that historically have been mediated by humans will be challenging. One challenge will be addressed by the availability of the digital twin of the organization sophisticated enough to adequately represent the way values and transactions flow through the business. But at any point, executives and line managers will need to drill down into this digital twin either to ensure the application is functioning properly or to effect changes. This is where new usability approaches like progressive disclosure come in — enabling users to move from abstract representations of information to very specific data points. While the best practices around progressive disclosure are still being defined, as enterprise technologists we have been designing software for decades that obscures the complexity of business processes and transactional relationships from users.

From the earliest days of service-oriented architecture to modern application programming interfaces (APIs) built around representational state transfer (REST), we are creating systems that know how to interact with less human involvement, completing processes across systems in ways that the designer of each system could not have envisioned. To help executives navigate all this uncertainty, we're going to need all the lessons we've learned from that evolution to deliver this vision of the digital twin.

A grey colored placeholder image