Data, data, data. There are about as many flavors of data as there are flavors of soda or brands of clothes. We even have a term for having copious amounts of data; “Big Data.” The word ‘data’ itself has become ubiquitous in the business environment to the extent that it has an ambiguous meaning.
In this post we’ll take away some of the ambiguity around data, and attempt to examine the impact of the ways in which we interact with, use, create, and store data, on the organization – from reporting structure to individual responsibilities.
Why is data important? How do we get it?
Over time, companies have increasingly measured more and more elements of their operations, using that data to drive improvement in processes, ultimately resulting in better output for stakeholders. With data-driven decision making, businesses compare historical and current performance, continually improving operations and processes. Businesses also use data to build forecasting models unique to their products, customers, and business environment. Ultimately data in various forms is used to support decision making about allocation of resources across the organization. Data is a powerful tool when wielded correctly.
In the modern enterprise, data is gathered in a few primary ways:
This is where Planners, Analysts, Coordinators, Liasons, etc. input their data into information systems manually through touch-type data entry, scanning barcodes and other information, and manual file uploads. Manual input is the most time consuming and potentially expensive data gathering method, but sometimes it’s the only option.
Here, systems do the manual labor for employees. By collecting information at the source and storing it in a database, they can then be integrated to share that information across the network instead of requiring manual input at each stage of the process. Automated input is how the vast majority of enterprise data is generated. Automating data input can reduce both staff costs and time required to get the data into the system.
System Generated Data:
This is a type of automated input where systems are synthesizing new information out of connections drawn from pre-existing data. A good example of this would be a forecast engine, or optimization system. Data synthesis systems vary greatly in cost, but significantly reduce the time required to make certain decisions or model scenarios.
How Data Impact’s People’s Roles
Data has many impacts on the organization. As an example, most companies have recently completed, or are in the midst of, their annual employee review process. One common trait across employee reviews in any organization is the concept of a Key Performance Indicator or KPI.
KPI’s are a piece of data that is used to correlate employee performance over time and compare that performance with personal and team goals. Think about a Sales Team – they have many data points which make up the KPI’s they use to drive growth, revenue, and profit, not to mention create plans and forecasts. As with any type of data used by the modern enterprise, KPI’s are ultimately used to determine how to allocate resources within the organization. Other examples of data use in the organization are Logistics, Operations, IT, Financial Indicators and Valuation, to name a few.
Data influences behavior as more than a measure – almost every employee in a modern enterprise is responsible for a certain amount of data, and interact with it in a multitude of ways. Think about all of these different positions in the data generation, analysis, and consumption chain:
- Data Entry Operators
- Data Analysts
- IT (Storage, Security, Distribution, Quality Control/Integrity)
- Executive review / Dashboards
- Strategic Planning
How does a change in the way we interact with data change the organization?
Now for the interesting part. Because the modern enterprise is so data-driven and data-centric, in an ideal system every change in the way data is used or interacted with will change the structure of the people organization around it.
Consider the concept of a “Business Transformation” for a moment. At recent conferences I’ve heard much discussion of the “Evolution” and “Transformation” of a business, but ultimately it came down to two simple paths; changing the data and changing the people. At o9 Solutions we have the perspective that no information system or deck of consulting slides will solve your problem, but with the careful application of the two in concert impressive value can be achieved.
The genesis of most business transformations is simple. An executive in one part of the organization champions an initiative to make a change.
Historically Supply Chain, Finance, or Sales have taken the lead, but it can start anywhere. This executive hears bottom-up feedback about a process that’s not working, or is informed that by measuring the business in a different way there’s value to be achieved, or simply a better technology comes along which improves interaction with the data. In various forms the organization audits itself in preparation for the change by cataloguing systems, processes, and people, then engages with the appropriate third-party support to enable the change to occur.
Over the course of transformation, companies take stock of what data is meaningful, and why. Teams dig into their processes and decide which is adding value, and where the inefficiencies lie. Ultimately a decision is made about what the future state will be, and the change begins. Here is where the rubber meets the road for the organization.
As the process, and therefore the data, changes to reflect the new goals of the organization, people quickly realize that this requires mirrored changes to the human element of the system. The human changes can play out in minor ways, such as sales teams having different territory assignments, or it can be major, with whole segments of leadership shuffling to reflect the structure required to support the new interaction between people, data, and technology.
In the case of integrated planning, organizations are having to accept an unprecedented level of complexity, interconnectedness, and visibility. In most cases, jobs get easier. The move from spreadsheets to planning and forecasting systems, for example, significantly reduces the manual labor of creating a plan and increases the expectation of success and accuracy. Executives will have better visibility into the real-time status of their responsibilities and can assign tasks accordingly.
However, this transformation can be stressful for teams who are being asked to interact with departments they’ve never worked with before, and being held responsible to common goals across traditionally siloed business functions. IT will have to learn new interconnections between systems, and release the carefully safeguarded data to increasingly more users. Executives may find themselves leading different, more diverse teams which serve multiple purposes. Each employee will be held increasingly more responsible to understand not only their role, but their piece in the great machine of the modern enterprise.
What are your thoughts?
I’d be interested to hear what you have to say about transformations in your business, systems, data, organization, or any of the like. This is but one opinion in the ocean of thought that is the professional community, and it is meant to stimulate conversation, not be a statement of hard fact.
At o9 Solutions we believe in a collaborative transformation of people, process, and technology in one simultaneous effort. If you’re considering a change on your team, we’d be happy to learn more about your goals and challenges, and share our opinion on a best path forward.