Fun fact: the average business today uses over 300 applications to run the enterprise. Employees shift between these apps every two to three minutes, and according to McKinsey, spend almost 50 percent of their time searching for information and managing communications. This is today’s digital workplace, and it is a beautiful and terrible thing. Technology gives us more options for communication and collaboration than ever before. But it comes at a cost unless companies prepare a clear technology blueprint that documents and visualises their entire digital workplace.

What price do organisations without a strategy pay? The decline of corporate memory. With so many people creating so much content in so many places, data gets stored in silos, never to be seen again. From local laptops to email, document repositories to old-school intranets, chat, text, Skype, Slack … the list goes on, and the knowledge gets lost forever.

The loss of corporate memory is more serious than it perhaps sounds. Corporations are living organisms, and similar to their natural counterparts, their culture is based on collective memory. Without the assets and interactions that drive an organisation on a day-to-day basis, culture would become almost impossible to pin down and communicate. Lack of a strong culture brings its own ramifications, from reduced productivity to low employee engagement to high turnover.

Fun fact number two: the loss of accumulated corporate knowledge costs companies an estimated $US430,000 per departing employee on top of the “usual recruitment replacement costs.” Corporate memory may sound like a fuzzy topic, but the numbers are anything but.

It feels like a catch-22: We need all these technologies to do our jobs, but they impede us from doing our jobs productively. How can we rein in the application sprawl of the digital workplace while ensuring we still have the tools that we need? I believe it starts by looking at the technology that makes up your digital workplace through the lens of your corporate memory. Instead of thinking about technology strategy as providing an app for every use case, think about how to connect all those apps so you can transform transient memory into persistent memory and help employees make better decisions, faster.

Here’s what this approach looks like in action:

1. Categorise Your Organisation’s Content

Not all content is created equal, nor does it all need to be stored and searchable. The first step to standardising your corporate memory and optimising your digital workplace is to organise company knowledge. Corporate content comes in three flavours:

Tacit knowledge: The approximately 40 percent of your corporate memory that lives in employees’ brains. Without a structure in place, that’s where it stays, and vanishes when an employee leaves.

Transient knowledge: The 10 percent of corporate information that goes back and forth. These are the messages, conversations and content that live in chat apps, in texts on employees’ phones, or in comments on collaborative docs. Trust me, some of the most impactful corporate decisions are made here, and never recorded.

Persistent knowledge: This accounts for the remaining half of your corporate memory, including all “official” corporate information that’s created with the intent of documenting and sharing knowledge. Employee and customer engagement systems (like corporate intranets, HR and CRM apps) fall into this category, as well as all the documents, spreadsheets, presentations and emails your employees constantly create. Persistent knowledge presents the biggest opportunity when it comes to organising and collating information across all your tools because much of it still remains in employees’ inboxes and document storage accounts.

Once your corporate knowledge is categorised, you can determine what is most critical to keep and what you can let fade away. The ongoing categorisation effort, however, should not be manual. Given the volume of data created in a digital enterprise, it’s crucial to categorise content automatically without expecting employees to tag or organise it. That means you need an analytics system that understands the content in realtime, extracts the appropriate context through people-topic modelling, and builds out organisational knowledge graphs with querying capabilities.

2. Create a Data Pipeline

To get there, you need to connect different sources of information and communication together by creating an end-to-end data pipeline. It should include the following functionality to scale out your analytics data streams:

• An information extraction system that pulls structured and unstructured information from different content sources across your organisation, like documents, text, images, videos, etc.
• A content analytics system that runs statistical and machine learning algorithms to correlate people and content relationships.
• A content enrichment stream that adds metadata to your content on-the-fly from complimentary data sources like HR management systems, knowledge graphs and domain graphs.
• A content lifecycle system that constantly reorganises and prioritises the content based on your organisational needs.

3. Build an Organizational Knowledge Graph

Once your data sources are connected and your content enriched, store it all in a centralised location. This is your hub for people and knowledge, the corporate “brain” at the centre of all your endpoints.

This is not a standard, linear document repository but an interconnected web that includes people, content and, most critically, the interactions between them. It houses knowledge, makes it easily and quickly discoverable, and eventually serves it up proactively based on preferences and realtime context. This core data structure should maintain all people-to-people, content-to-content and people-to-content relationships across your organisation.

4. Add Context

Once your people and content are connected, you need to add context to ensure that discovering them is fast and effective. This starts with semantic search. Your hub’s search capabilities should be predicated on your organizational domain, content and people with automatic contextualisation. A semantic search understands the intent of your search instead of just mapping a keyword to indexed content. For example, a search for “Tesla” should return very different results when you are shopping for a car versus in a library searching for patents. These types of distinctions are a key requirement for having a strong, standardised corporate memory.

5. Go Next-Gen

To create a truly successful digital workplace, the intelligence at the centre of your corporate memory should evolve from descriptive to predictive and eventually prescriptive. That means that employees can not only search and find knowledge, but have it recommended to them, in context, when and where they need it. The real value of search is when you don’t have to search: the system’s AI will know what you need, when you need it, and deliver it accordingly.

A digital workplace is far more than a collection of apps that allows us to work remotely. It can be either a destroyer or enabler of your corporate culture and memory. As such, your blueprint to a successful digital workplace should focus not on which tools you need to solve individual use cases, but on how to connect all of those use cases and the people behind them in a meaningful — and powerful — way.

Tej Redkar has been building enterprise software products for more than 20 years, and recently joined Aurea Software as chief product officer. He’s led engineering, product management, user experience and data science teams several times in his career for industry leading organizations like Hitachi, IBM, VMware, Microsoft, Cisco and AppDynamics.