Can you make your facility more predictable?

Dr Hennie Ras, WSP Facilities Management

20/10/2010

Understanding what Facilities Management is all about

No Published Definition Reference

1 the development, co-ordination and control of the non-core specialist services necessary for an organization to successfully achieve its principle objectives

US Library of Congress 1989

2 refers to buildings in use, to the planning, design and management of occupied buildings and their associated building systems, equipment, and furniture to enable and to enhance the organization’s ability to meet its business or programmatic objectives

Becker 1990

3 an integrated approach to maintaining, improving and adapting the buildings of an organization in order to create an environment that strongly support the primary objectives of that organization

Barret 1995

4 the process by which an organization ensures that its buildings, systems and services supports core operations and processes as well as contribute to achieving its strategic objectives in a changing conditions

Alexander 1996

5 the integration of multi-disciplinary activities within the built environment and the management of their impact upon people and the workplace

BIFM 2001

Understanding what Facilities Management is all about (continued)

• Note that all definitions, except no.1, assumes the workplace to be contained within the building.

• Facilities Management is concerned with both tangible aspects of a facility (e.g. building, systems, equipment), as well as non-tangibles such as environmental/social/political/economic influences, process design, and third party services

• The way we think and talk about Facilities Management determines our mental model of how Facilities Management works.

• What is your model for Facilities Management?

Statistically meaningful prediction of the performance of facilities

• Possible the most studied and mature predictions are weather and atmospheric patterns.

• These predictions increased in their accuracy due to the availability of powerful computing devices, as well as a realisation that weather predictions are very sensitive to initial conditions.

• Two kinds of common prediction errors:– Model inadequacies– Uncertain initial conditions

• Can improve prediction by:– Improving the model– Improving the observational network to reduce errors in the initial

conditions

Statistically meaningful prediction of the performance of facilities (continued)

FM Model Variables Example Measurement

Temperature Cold storage, fridge, office Direct

Electricity Consumption Fan motors, heater elements, lights Direct

Cash Flow Invoices, journals, ledger In-direct from financial reporting

Time to Respond Maintenance SLA, Expiry dates, Enquiries

Direct and In-direct from financial reporting

Location Churn, Assets on the move In-direct from financial reporting

Item Status On/Off, Cold/Hot, Open/Close, Full/Empty

Direct

Supplier Reliability Accuracy of orders, strikes, delays In-direct from financial reporting

Service/Product Quality Conformance to Specifications Indirect via specialized testing on sampling basis

Social/Political/Economical influences

Interest rates, exchange rates, fuel price, regulations, tax rates

Indirect via institutional reporting

• Direct measurements tend to be quantitative and immediate• Indirect measurements tend to vary from quantitative to semi-quantitative

and/or qualitative and delayed• Each variable has its own pattern of variability• Prediction of the behaviour of a facility now becomes more “soft” due to

qualitative nature of data and cumulative effect of multiple variability• Prediction accuracy depends on:

– the appropriateness of the FM model (including all direct and in-direct variables and knowing their contribution to facility behaviour)

– Knowing initial values for each variable (including qualitative variables)• Weather prediction may be an easier problem to solve!

Statistically meaningful prediction of the performance of facilities (continued)

Making the facility more predictable

• Predictability is closely related to Visibility and Control (Atkin 2009)

• Therefore, increase Visibility to increase Control to improve Predictability

• Implement real time visibility and control on variables that can be directly measured

• Implement business process visibility and control on variables that can be measured in-directly, often possible in near-real time

• Provide operational policies and guidelines for variables that can only be measured through institutional reporting

Making the facility more predictable (continued)

Central Visibility Dashboard

Automated Data Capture System

Barcode Labels

RFID Tags

Electronic Sensors:Biometrics, Temp, volume, pressure, movement, etc

Business Processes

Command & Control Feedback

Command & Control Feedback

Useful technologies in providing visibility to FM operations

• Item level identification• Mobile handheld devices• SCADA loggers and controllers• Electronic workflow• Services oriented system architectures (SOA)• International and Local governance frameworks and

standards

Mobile handheld devices

SCADA loggers and controllers

Electronic workflow

Identify AssetLink Item Level code

Identify PersonApply Depreciation

ReportingLogin

Asset Management

Identify ItemLink Item Level Code

Identify PersonAuthorise Despatch

ReportingLogin

Supply Chain Handling

Services oriented system architectures (SOA)

Identify AssetIdentify Item

Authorise DespatchLink Item Level code

Identify PersonApply Depreciation

Presentation

Visibility Platform

Orchestration

Services oriented system architectures (SOA) (Continued)

Frameworks and Standards

King IIISOXSARSPFMAMFMASA Institute for Chartered Accountants

Designing liability and accountability into FM processes

• Liability - A comprehensive legal term that describes the condition of being actually or potentially subject to a legal obligation

• Accountability - The obligation imposed by law or lawful order or regulation on an officer or other person for keeping accurate record of property, documents, or funds. The person having this obligation may or may not have actual possession of the property, documents, or funds. Accountability is concerned primarily with records. While responsibility is concerned primarily with custody, care, and safekeeping.

Designing liability and accountability into FM processes

• We refer to the operational manifestations of liability and accountability when an employee signs for receiving or accepting or handing over work-in-progress, or a document, or an item of value.

• Such signature can be in handwriting, a biometric or a personal code or password, all of which are unique to each and every individual employee

• Such signatures are often prompted by electronic workflow driven processes

• For auditability these signature events are stored on a central database and reported as a Chain of Custody report per item, process or employee

Summary and Conclusion• What does your model of Facilities Management look like?• Weather prediction may be an easier task due to the availability

of standardized models, algorithms and available atmospheric measurement data

• In FM we can at least improve visibility of the performance of facilities by capturing item level performance data and process performance data.

• Automated data capture technologies will assist greatly in improving FM data integrity.

• Visibility and predictability of FM leads directly to more effective and efficient facility performance due to enhanced command and control, as well as enhanced process liability and accountability.

Questions• References:

– Alexander, K. 1996, Facilities Management. In Facilities Management: Theory and Practice, edited by Alexander K., (London: E & FN Spon), pp. 1-13

– Atkin, A. And Brooks, A.,2009, Total Facilities Management, 3rd edition, Blackwell Publishing Ltd, Chapter 12.

– Barret, P., Facilities Management: Towards best Practice, (Oxford: Blackwell Science)

– Becker, F., 1990, The Total Workplace: Facilities Management and the Elastic Organisation, (New York, Van Nostrand-Reinhold)

– BIFM, 2001, see Alexander , K. et al, Facilities Management: Innovation and Performance, Spon Press, 2004, p. 83

– Information Theory and Predictability, Lecture 8: Statistical Probability, www.math.nyu.edu/faculty/kleeman/infolect8.pdf, accessed 7 October 2010

– Internal documents in WSP supporting discussion of using automated data capture in Facilities Management

– US Library of Congress 1989, see Alexander , K. et al, Facilities Management: Innovation and Performance, Spon Press, 2004, p. 83